Data Modeling

Data Modeling Developer Jobs

138 jobs found

1d ago

Data Engineer IV

Hudson Manpower Cincinnati, OH

Cincinnati, OH

1d ago

$68 - $70/hr Full time AWS Big Data Cloud

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Job Description

What you get at this onsite Data Engineer IV position in Cincinnati, OH include a competitive base pay of USD 68 - 70 per hour, comprehensive medical, dental, and vision coverage, optional life and disability insurance, a 401(k) plan with company match and potential profit sharing, paid vacation time, paid bench time, a training allowance, and referral bonuses. You will join Hudson Manpower and focus on building scalable data pipelines that power machine learning models deployed in AWS SageMaker, collaborating within the Machine Learning Data Enablement squad of the Data Insights Tribe.

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance provided
401(k) with a company match and optional profit sharing
Paid vacation time
Paid Bench time
Training allowance offering
Referral bonuses

Responsibilities

Join the Machine Learning Data Enablement squad in the Data Insights Tribe.
Help build high quality, scalable data pipelines that power machine learning models across the enterprise, deployed in AWS SageMaker.
Deliver curated, production-ready datasets in collaboration with data scientists and ML engineers.
Work closely with data scientists and ML engineers to shape how machine learning data is delivered across the bank.
Maintain in-office presence: in office 4 days a week minimum (Monday-Thursday).
Help define how data powers machine learning at scale.

Requirements

Proficiency in Python
Proficiency in SQL
Location: Cincinnati, OH - onsite
USC and GC Holder candidates only
In-office 4 days a week minimum (Monday-Thursday)

Technologies

Python
SQL
AWS Sagemaker
DBT
Snowflake
Databricks

Top skills

Python
SQL
AWS Sagemaker
DBT
Snowflake

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2d ago

Senior Data Engineer

firstPROPhiladelphia Philadelphia, PA

Philadelphia, PA

2d ago

$60 - $70/hr Contract Senior Analytics Automation

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Job Description

The contract-to-hire Senior Data Engineer focuses on real-time streaming data pipelines for connected medical devices, operating in a hybrid environment in Philadelphia. The role leverages Azure Databricks, Azure services, and ML/AI data workflows. Compensation ranges from USD 60 to 70 per hour.

Responsibilities

Design and implement batch and streaming data pipelines on Azure and Databricks, with emphasis on real-time IoT telemetry within a Medallion architecture.
Create ETL/ELT workflows to ingest, transform, and validate large volumes of structured and unstructured data.
Develop and maintain data services, APIs, and microservices for application, analytics, and ML/AI teams.
Deploy real-time streaming solutions using Azure Event Hubs, Azure Stream Analytics, and related Azure integration patterns, focusing on cost-effective throughput, proper partitioning, and downstream delivery to Databricks.
Optimize production Databricks pipelines with PySpark, Spark SQL, and Delta Lake, including tuning for performance, reliability, and cost.
Troubleshoot and resolve complex pipeline issues across Databricks, Azure, and on-premises systems, including root cause analysis and corrective actions.
Collaborate with data analysts, software engineers, ML engineers, and business stakeholders to translate requirements into technical designs and delivery priorities.
Apply data quality, validation, and privacy-first practices, delivering reliable pipelines through software engineering standards, documentation, testing, and CI/CD.

Requirements

Bachelor's degree in Computer Science, Mathematics, Engineering, or a related technical field with 6+ years of professional experience in data engineering, analytics, or warehousing; or Master's degree in a related field with 3+ years of experience.
5+ years designing, building, and operating big data and real-time streaming pipelines across cloud and on-premises environments.
5+ years applying DevOps and CI/CD practices to data and analytics workloads.
Production experience building data services, APIs, or microservices for downstream data consumption.
Strong hands-on experience designing and building production-grade data pipelines on Databricks.
Demonstrated experience with Spark optimization and tuning in Databricks, including performance analysis, partitioning strategies, caching, shuffle optimization, and cost-aware pipeline design.
Strong experience with Azure cloud services for data engineering and streaming workloads.
Data quality, validation, and privacy-aware handling for regulated or sensitive data.

Technologies

Databricks
Spark
PySpark
Spark SQL
Delta Lake
Azure
Azure Event Hubs
Azure Stream Analytics
Azure Databricks
Medallion architecture

Outcomes

Onboard to the Azure Databricks environment and contribute to troubleshooting, stabilization, and optimization of existing batch and streaming data pipelines.
Stand up Azure streaming ingestion for telemetry data and deliver production-ready pipelines integrated with Databricks to support API, ML, and downstream analytics consumption within the Medallion architecture.
Design and deliver data services or consumption patterns that enable business and ML teams to access near real-time telemetry data reliably, securely, and at scale.

Work Hours and Travel Requirements

Willingness to assist in troubleshooting and analysis during off-hours production issues as needed.
The IT team operates in a hybrid environment requiring a minimum of two days per week in the downtown Philadelphia office.

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2d ago

Database Developer

SOUTHEASTERN COMP CONSULTANTS INC Dahlgren, VA

Dahlgren, VA

2d ago

Full time Senior Cloud Architecture Data Architecture

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Job Description

This Database Developer role at SCCI centers on designing and implementing a unified enterprise data architecture across a complex system landscape, defining ontology, data standards, and modeling to govern and scale data across the organization. The position is based on site in Dahlgren, VA.

Overview

SCCI seeks a Database Developer to lead the design and implementation of a unified enterprise data architecture across a broad ecosystem of programs and platforms. The role involves defining how data is structured, governed, and scaled, while operating at both strategic and hands-on levels to establish standards, guide implementations, and tackle intricate data integration challenges. This position is based in Dahlgren, Virginia.

Responsibilities

Lead enterprise data ontology development, including core entities, relationships, and semantic standards; create canonical data models that unify disparate systems; establish enterprise data standards, naming conventions, and modeling guidelines; serve as the authoritative source on data structuring and governance.
Design complex logical and physical data models across multiple domains; architect solutions balancing normalization, performance, scalability, and usability; define patterns for structured, semi-structured, and unstructured data; guide teams in implementing consistent, reusable data structures.
Manage cross-system alignment by reconciling conflicting data models, crafting integration strategies for interoperability, defining data contracts and interface schemas between services, and eliminating redundancy and inconsistency across datasets.
Develop frameworks for structuring and integrating unstructured and semi-structured data; specify metadata tagging and classification approaches to support discoverability and governance; evaluate when to leverage relational, NoSQL, or hybrid approaches.
Establish and enforce data governance standards, including data quality, lineage, and validation rules; collaborate with stakeholders to define authoritative sources and master data domains; implement data auditing, traceability, and compliance measures.
Architect high-performance data solutions capable of supporting enterprise-scale workloads; lead performance tuning across databases, queries, and pipelines; design for scalability in cloud and hybrid environments.
Provide technical leadership to database developers and data engineers; review designs and implementations for alignment with enterprise standards; mentor team members in data modeling, database design, and best practices; influence technical direction across multiple teams and programs.
Collaborate with enterprise architects, application developers, and business stakeholders; translate domain needs into scalable data architectures; lead design reviews and communicate complex data concepts clearly.

Essential Skills and Experience

Must be a U.S. citizen and able to obtain and maintain an active Secret Security Clearance.
Bachelor’s degree in Information Systems, Computer Science, Engineering, Math, or a related technical field.
Seven to twelve plus years of experience in database development, data engineering, or data architecture.
Deep expertise in relational database design and advanced SQL.
Proven track record designing enterprise-scale data models and architectures.
Strong experience integrating data across multiple systems and domains.
Demonstrated ability to structure and model unstructured and semi-structured data.
Experience with ETL or ELT pipelines and large-scale data transformation.
Solid understanding of data governance, data quality, and data lifecycle management.

Preferred Skills and Experience

Active Secret Security Clearance.
Experience building or contributing to enterprise data ontologies, semantic layers, or knowledge graphs.
Familiarity with Master Data Management and canonical data modeling approaches.
Experience with cloud data platforms (AWS, Azure, GCP) and modern data stacks.
Knowledge of data cataloging and metadata management tools.
Experience with distributed systems and event-driven architectures.
Programming experience in Python, Java, or similar languages for data processing and automation.

Technologies

Python
Java
AWS
Azure
GCP
Relational databases
NoSQL

Benefits

Health, dental, vision, life and disability benefits
401(k) with Company Match
Paid vacation (2 weeks)
Sick and personal leave (48 hours)
11 paid holidays

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2d ago

Data Engineer (SMTS / LMTS) - MDM

Salesforce San Francisco, CA

San Francisco, CA

2d ago

$149k - $286k/yr Full time Senior Ai Ml Artificial Intelligence

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Job Description

Salesforce seeks a Data Engineer at the Senior or Lead Member of Technical Staff level within MDM to design, build, and operate Master Data Management capabilities, including entity resolution, golden records, and hierarchy automation, while guiding technical strategy and leveraging AI powered tooling.

Responsibilities

Design, develop, and sustain AI driven developer tools, engineering automation, and productivity accelerators using modern AI platforms such as Claude, Cursor, Windsurf, and GitHub Copilot, among others
Build and maintain end-to-end MDM integrations, including MuleSoft connections, Airflow workflows, API orchestration, event-driven architectures, Change Data Capture, and batch processing pipelines
Implement entity resolution, golden record lifecycle management, hierarchy processing, data quality validation, and governance capabilities
Integrate with third party data providers such as Dun & Bradstreet, Moody's, and Leadspace to support data enrichment and corporate hierarchy management
Design and optimize data models, database schemas, APIs, and integration patterns to meet MDM needs across hierarchical, relational, and party data structures
Deliver production-grade solutions with robust monitoring, alerting, operational supportability, and security by design
Promote AI assisted software engineering practices to improve developer productivity, testing efficiency, and delivery speed
Participate in design reviews, code reviews, operational readiness reviews, and release activities
Troubleshoot complex production issues, perform root cause analysis, and implement scalable long-term fixes
Collaborate effectively with globally distributed teams across multiple time zones
LMTS additional: Architect and evolve end-to-end MDM integration systems and define technical strategy for entity resolution, golden record lifecycle, hierarchy management, data quality, and governance across multiple business domains
LMTS additional: Lead design reviews and establish engineering standards for scalability, observability, resiliency, security, testing, and operational excellence
LMTS additional: Partner with PMs, Product Owners, TPMs, and business stakeholders to define architecture, roadmap priorities, solution designs, and delivery plans aligned with business objectives
LMTS additional: Provide technical leadership across internal engineering and systems integrator teams

Requirements

Minimum Qualifications — SMTS

8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms
10+ years of progressive experience in enterprise integration, data engineering, MDM, or large-scale data platform development
Proven experience using modern AI assisted development platforms such as Claude, Cursor, Windsurf, GitHub Copilot, or similar to boost engineering productivity
Strong understanding of Generative AI and agentic workflows and their practical application within software engineering
Hands-on experience with Informatica SaaS MDM, particularly with party data models including Account, Contact, Organization, and Supplier
Hands-on development experience with Java, REST APIs, microservices, and enterprise integration patterns
Experience designing and building API orchestration layers, MuleSoft integrations, microservices, and event-driven architectures
Experience with Kafka or similar event-streaming technologies, CDC, and event-driven architectures
Experience with AWS, GCP, or Azure cloud services and cloud-native application development
Strong knowledge of SQL, data modeling, database design, and distributed data processing architectures
Excellent communication and collaboration skills
A related technical degree is required

Minimum Qualifications — LMTS

10+ years of progressive experience in enterprise integration, data engineering, MDM, or large-scale data platform development
Deep expertise in MDM concepts including entity resolution, golden record lifecycle, match/merge/survivorship, data quality, governance, and hierarchy management
Proven experience designing and building API orchestration layers, MuleSoft integrations, microservices, and event-driven architectures
Proven experience building developer tools using modern AI tech stacks such as Claude, Cursor, and related tools in the MDM domain
Demonstrated technical leadership, cross-functional collaboration, and the ability to drive multiple complex initiatives from design through delivery
Excellent communication skills with the ability to influence stakeholders across all levels

Even Better If

Experience with Salesforce Data Cloud, CRM platforms, or broader Salesforce ecosystem technologies
Experience handling corporate hierarchy data from Dun & Bradstreet, Moody's, or Leadspace, including family tree traversal, DUNS resolution, monitoring, and registration workflows
Experience building Python based data engineering frameworks and automation solutions
Experience with data stewardship, governance processes, and operational data quality tooling
Experience with Retrieval-Augmented Generation (RAG), vector databases, AI agents, MCP frameworks, or related AI technologies
Experience building internal developer platforms, engineering productivity tools, or agentic solutions supporting enterprise engineering teams
Demonstrated track record of driving measurable engineering productivity improvements through AI enabled tooling and automation
Certifications in MDM, data management, cloud platforms, MuleSoft, Informatica, or related technologies

Technologies

Claude
Cursor
Windsurf
GitHub Copilot
MuleSoft
Airflow
Kafka
AWS
GCP
Azure
Informatica SaaS MDM
Java
REST APIs
Microservices
Python
Salesforce Data Cloud

Benefits

Time off programs
Medical
Dental
Vision
Mental health support
Paid parental leave
Life and disability insurance
401(k)
Employee stock purchasing program

Location

San Francisco, CA (onsite)

Job Category

Software Engineering

Compensation

USD 148,500 - 285,800 per year

About Salesforce

Salesforce positions itself as a leading AI enabled CRM where people and AI agents come together to drive customer success. The company emphasizes turning ambition into action, technology into trust, and innovation into a core operating principle. Salesforce seeks Trailblazers who are committed to advancing business and society through AI while upholding its core values.

If you aim to advance your career at a company shaping workforce transformation in the AI era, this is a place to explore. The organization views Agentforce as the future of AI and invites engineers to contribute to Salesforce's ongoing AI initiatives.

The Experience

Salesforce is building a comprehensive understanding of business relationships across its global customer ecosystem. A key pillar is Master Data Management, which identifies, enriches, deduplicates, and governs every business entity and corporate hierarchy the company engages with. The team is seeking SMTS and LMTS engineers to design, develop, and operate essential MDM capabilities such as entity resolution, golden records, and corporate hierarchy automation, while leveraging modern AI technologies to create developer tools, automation, and productivity accelerators.

At LMTS level, the role includes shaping technical strategy for end-to-end platforms and providing cross-functional leadership. At SMTS level, the role emphasizes hands-on technical leadership with a focus on translating architecture into scalable, production-grade systems. Both paths collaborate closely with Product Management, Data Governance, Architecture, Systems Integrator partners, and downstream consuming teams.

Accommodations

If you require a reasonable accommodation during the application or recruiting process, please submit a request through the Accommodations Request Form.

Unleash Your Potential

Joining Salesforce offers broad support for work life balance and personal growth, with benefits and resources to help you thrive. The company emphasizes AI enabled impact to accelerate outcomes and the pursuit of delivering exceptional experiences for customers and users.

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2d ago

Lead Data Engineer

Wolverine Worldwide Remote 🌍 Remote

Remote

2d ago

$120k - $158k/yr Full time Analytics Azure Azure Data Factory

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Job Description

Wolverine Worldwide offers a 100% remote Lead Data Engineer role with a competitive annual salary range of USD 120,000 – 157,500. In this position you will lead the design, development, and deployment of Microsoft data solutions using Microsoft Fabric and the Azure data platform, mentor junior engineers, and drive data governance across cloud environments.

Responsibilities

Serve as the technical lead for modern data engineering initiatives, emphasizing Microsoft Fabric and Azure Synapse Analytics, and covering data pipelines, notebooks, lakehouse architectures, and enterprise data warehousing platforms.
Guide cross functional teams to design, implement, and provide hypercare support for contemporary data warehousing solutions from inception to operation.
Collaborate with management, customers, and colleagues to determine and refine requirements.
Provide estimates of resources, timelines, and costs for multiple projects across diverse teams.
Offer guidance on data governance, security, and privacy across cloud environments.
Lead or assist with problem solving related to application performance, usage, and general support activities for customers and team members.
Create system documentation, user manuals, and deliver or facilitate user training sessions.
Own disaster recovery initiatives and enforce change management standards and procedures.
Set and monitor service delivery levels, focusing on reliability, availability, accuracy, maintainability, and cost.
Support IT leadership in shaping and executing complex objectives aligned with short and long term company goals.
Evaluate third party solutions, stay current with technologies and trends, and integrate relevant innovations into the environment.
Continue developing technical and business proficiency through self-directed study, project work, and vendor interactions.
Provide 24 hour on call support, including evenings and weekends.
Perform duties in line with the company AAP and EEO policies and contribute to broader organizational goals.
Take on additional duties as assigned by management.

Requirements

Bachelor’s degree in Computer Science or a related field, or equivalent work experience.
8+ years of proven experience in designing and implementing data warehouse architecture, data delivery, data modeling, ETL tools, master data management, and deploying automated, well-documented solutions.
5+ years of experience with Microsoft cloud data platform solutions, including Microsoft Fabric OneLake, Azure Synapse, DevOps, Data Factory, pipelines, and notebooks.
Experience with monitoring and optimization tools such as Azure Monitor, Application Insights, Fabric capacity metrics, or equivalents.
Medallion Architecture modeling experience.
Proficiency in Python for data processing (dataframes, Spark, etc.) and SQL development with performance optimization.
Power BI experience is a plus.
Strong communication, analytical, problem solving, and organizational skills.
Ability to establish and maintain effective working relationships at all levels of the organization.
Ability to mentor other team members in cloud technologies.
Remote work capability with preference for candidates located in Michigan.

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3d ago

Data Engineer – Corporate Technology Data Engineering & Analytics

MassMutual Boston, MA

Boston, MA

3d ago

$134k - $176k/yr Full time Analytics Big Data Business Analytics

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Job Description

As a Data Engineer within MassMutual’s Corporate Technology Data Engineering & Analytics team in Boston, MA on a hybrid schedule, you will help design and implement ELT pipelines, data marts, and data warehouse solutions to support Investment Management. You will work closely with analysts, architects, and business stakeholders to translate requirements into scalable data solutions.

Responsibilities

Design, build, and assess intricate ELT workflows that consolidate diverse data sources into high-integrity, reliable data assets.
Contribute to data modeling policies, procedures, and standards, providing actionable feedback.
Capture and document system flows and other technical details about data, database design, and related systems.
Establish comprehensive data quality standards and implement effective tools to ensure data accuracy and reliability.
Collaborate with Investment Management teams to understand new data patterns and requirements.
Work with Data Analysts, Data Architects, and BI developers to deliver scalable data solutions aligned with business goals.
Translate high level business requirements into detailed technical specifications.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems or a related technical field.
Eight or more years of experience in data analytics, data modeling, and database design.
Five or more years of experience with ELT methodologies and tools.
Five or more years of experience in designing, developing, tuning, and troubleshooting SQL.
Three or more years of coding and scripting experience in Python, Java, or Scala, including design work.
Two or more years of experience with the Spark framework.

Technologies

Python
Java
Scala
SQL
Spark
Informatica PowerCenter
Informatica IDMC
Vertica
Snowflake
Power BI
Tableau
Blackrock Aladdin
CRD
Eagle STAR
Eagle Pace
Eagle DataMart
GoldenSource
FINBOURNE
NeoXam
RIMES
JPM Fusion

Benefits

Paid Time Off including vacation, holidays, flexible holidays, and take care time for personal or family needs.
Health & Well-Being medical and dental coverage, mental health resources, and access to health coaching.
Financial Well-Being competitive compensation with 401(k) options and company match.
Taking Care maternity and parental leaves, bereavement leave, and caregiver leave up to 320 hours.
Giving Back three paid volunteer days and MassMutual Foundation donation matching up to $5,000 annually.
Commuter Benefits qualified commuter program and wallet options for eligible campuses in Boston and NYC.

Overview

A career at MassMutual means collaborating with exceptional colleagues and pursuing professional and personal growth. Our employees are foundational to delivering on our purpose of helping people secure their futures and protect what they love, and the culture emphasizes support and recognition for who you are.

Award-Winning Culture

MassMutual operates with a purpose driven by mutuality and a commitment to financial well-being for all Americans. The company aims to foster a thriving community where everyone feels valued, included, and that they belong. We Live Mutual in practice and aim to empower people to protect one another.

How We Work

MassMutual combines in-person collaboration with the flexibility of remote work. The hybrid model emphasizes in-office collaboration at least three days per week, while offering remote Fridays, company-wide remote weeks, and a bank of flexible remote weeks throughout the year.

Benefits For the Whole You (And Your Loved Ones)

We take a holistic view of compensation and benefits to support life beyond work. In addition to medical and dental coverage and a 401(k) with company match, we offer generous time off and unique programs designed to support well-being, caregiving, volunteering, and personal development.

Paid Time Off ample vacation, holidays, and take care time for health and well-being.
Health & Well-Being personalized health resources and support for mental and physical wellness.
Financial Well-Being robust retirement benefits and educational assistance.
Taking Care extended leave options for maternity, parental needs, and caregiving obligations.
Giving Back structured volunteering opportunities and charitable giving programs.
Commuter Benefits pre-tax commuting options and campus-specific wallet programs.

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3d ago

Sr Data Engineer

Subway Shelton, CT

Shelton, CT

3d ago

$103k - $128k/yr Full time Senior Apache Airflow Big Data

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Job Description

The Sr Data Engineer is a senior technical leader accountable for designing, building, and evolving Subway's enterprise data platform on Snowflake or Databricks. The role delivers reference implementations, proofs of concept, and platform-level solutions across multiple data domains.

Responsibilities

Design and implement reference architectures and production-grade frameworks on Databricks or Snowflake.
Architect lakehouse platforms using Delta Lake or Iceberg with a Medallion (Bronze/Silver/Gold) pattern.
Define and evolve enterprise data standards, patterns, and reusable accelerators.
Ensure solutions align with data governance, security, scalability, and cost-efficiency standards.
Conduct hands-on technology benchmarking to evaluate options beyond vendor presentations.
Develop the first working versions of complex pipelines, frameworks, and POCs for ingestion, CDC, streaming, data quality, observability, and CI/CD.
Drive emerging technologies from POC to production, including Iceberg, Lakeflow, Openflow, Cortex, and Mosaic AI.
Address high-complexity performance, cost, and governance challenges at petabyte scale.
Identify and remediate systemic technical debt and architectural risks.
Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex.
Partner with Data Science and Analytics teams to operationalize models and AI workflows.
Collaborate with Product, Architecture, Security, Infrastructure, and Analytics leaders.
Translate business needs into technical direction supported by working prototypes.
Communicate trade-offs, risks, and decisions clearly to technical and non-technical stakeholders.
Influence roadmaps and platform investments through technical insight and de-risked POCs.
Mentor Senior and Staff Data Engineers through pair programming, PR reviews, and design coaching.
Raise engineering maturity by shipping working examples and codifying patterns.
Foster a culture of technical excellence, learning, and continuous improvement.

Requirements

Location: Shelton, CT onsite
Minimum 3 years of professional data engineering experience
Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degree preferred
Exceptional hands-on expertise with Databricks or Snowflake lakehouse platforms
Proficiency in PySpark or advanced SQL, plus Python for data engineering and automation
Experience building Medallion architectures with Delta Lake or Iceberg
Real-time and batch streaming experience (Lambda or Kappa) with Databricks DLT or Snowflake Dynamic Tables / Snowpipe Streaming
Hands-on with orchestration tools such as Airflow, Databricks Lakeflow, or Snowflake Openflow; dbt experience is a plus
Strong data modeling skills (Dimensional, Data Vault, schema design)
Performance and cost tuning expertise (clustering, partitioning, Z-ordering, warehouse sizing, FinOps)
Governance experience with Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, and data quality
Semantic layer experience using Databricks AI/BI Genie / Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
AI/ML enablement experience with Databricks Mosaic AI or Snowflake Cortex
CI/CD and DevOps fluency — Git, Databricks Asset Bundles or Snowflake CLI / Schemachange, automated testing
Cloud ecosystem expertise — AWS (S3, Glue, Kinesis), Azure, or GCP
Excellent communication and technical storytelling abilities
Comfortable operating amid ambiguity and in complex stakeholder environments

Technologies

Databricks, Snowflake
Delta Lake, Iceberg
Medallion architecture, PySpark, SQL, Python
Databricks Structured Streaming / DLT, Snowflake Dynamic Tables, Snowpipe Streaming
Airflow, Databricks Lakeflow, Snowflake Openflow
dbt, Unity Catalog, Horizon Catalog
Databricks Mosaic AI, Snowflake Cortex
Git, Databricks Asset Bundles, Snowflake CLI, Schemachange
AWS, Azure, GCP (S3, Glue, Kinesis)

Benefits

Medical insurance
Life insurance
Retirement plan (401K/RSP)
Bonus
Mobility allowance
Tuition reimbursement
Paid holidays
Volunteer time off

About the Role

The Sr Data Engineer serves as a senior technical authority and builder, responsible for shaping Subway's enterprise data platform on Snowflake or Databricks. This role drives lakehouse architecture, engineering frameworks, and best practices across multiple data domains, operating with a high degree of autonomy and delivering reference implementations, POCs, and platform-level capabilities.