Data Strategy

Data Strategy Developer Jobs

6 jobs found

Today

Data Engineer Principal

Cummins Inc. Columbus, IN

Columbus, IN

Today

$131k - $160k/yr Full time Manager Analytics Big Data

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Job Description

Lead enterprise data platform strategy and engineering to support scalable analytics, AI, and business intelligence for Cummins in Columbus, Indiana.

Responsibilities

Own the strategy, architecture, and ongoing evolution of enterprise data platforms enabling analytics, AI, and business intelligence.
Partner with business leaders, product teams, and technical stakeholders to translate complex requirements into high-value data solutions.
Design and optimize data lake, lakehouse, data warehouse, and cloud-based architectures to improve accessibility, data quality, and performance.
Deliver resilient, reusable data pipelines that reduce time-to-insight and accelerate enterprise decision-making.
Establish and champion data governance, security, compliance, and quality standards for trusted enterprise data assets.
Drive continuous improvement for scalability, operational efficiency, cost optimization, and platform performance.
Provide technical leadership, mentoring, and architectural guidance to data engineering teams while promoting engineering excellence.
Enable executive and business-critical decisions by integrating and delivering data from diverse enterprise systems.

Requirements

Proven experience architecting and delivering enterprise-scale data platforms, data models, and cloud-based analytics solutions that support business growth and innovation.
Deep expertise in modern data engineering practices including scalable pipeline development, data integration, data modeling, distributed processing, and cloud-native architectures.
Strong leadership and stakeholder management skills to influence cross-functional teams, handle ambiguity, and align technology decisions with business outcomes.
Advanced knowledge of data governance, security, compliance, and modern software engineering practices, including Agile, DevSecOps, CI/CD, and automation.
10+ years of progressive experience in data engineering, data architecture, analytics engineering, or a closely related technical field, including leadership of complex enterprise data solutions.
Demonstrated delivery experience across large, complex manufacturing and supply-chain environments, with exposure to areas such as planning, procurement, manufacturing, inventory, logistics, engineering, aftermarket, commercial, finance, or related operational functions.
Ability to work directly with business stakeholders to understand complex problems and processes, clarify requirements, explore available data, and validate approaches using prototypes or proof-of-concepts before scaling to production.
Hands-on expertise with SQL and Python/PySpark, including data modeling, scalable pipeline design, data integration, and distributed or cloud data platforms.
Experience building and operating batch and streaming or near-real-time pipelines, including orchestration, reliability, monitoring, recovery, scalability, and performance.
Experience integrating data across complex enterprise sources such as ERP and operational systems, legacy apps and databases, APIs, cloud platforms, event streams, and IoT or telemetry sources, including structured or unstructured data.
Demonstrated experience designing and evolving enterprise-scale analytical architectures including data lake, lakehouse, data warehouse, or comparable platforms.
Strong data modeling experience across relational, dimensional, and enterprise/domain modeling, including fact and dimension structures, star/snowflake schemas, conformed dimensions, and patterns supporting analytics, operational, and AI use cases.
Experience creating reusable data engineering frameworks, shared foundations, enterprise data models, and governed data products supporting multiple use cases.
Experience with modern enterprise data platforms such as Databricks, Snowflake, and Azure data services or comparable cloud/data technologies.
Proven ability to lead full lifecycle delivery: discovery and requirements, data exploration, architecture, implementation, production deployment, monitoring, optimization, and ongoing support.
Ability to collaborate across Business, Data Science, AI Engineering, Analytics, Enterprise Architecture, and application and platform teams to deliver scalable technical solutions.
Experience providing technical leadership: architecture guidance, design reviews, engineering standards, solution trade-off decisions, and mentoring/coaching engineers.
Understanding of data engineering and architecture foundations needed to support advanced analytics, machine learning, GenAI, and AI-enabled solutions while maintaining standards for quality, governance, security, scalability, reuse, performance, and cost.

Technologies

SQL
Python
PySpark
Agile
DevSecOps
CI/CD
Data lake
Lakehouse
Data warehouse
Databricks
Snowflake
Azure data services
ERP
APIs
Event streams
IoT/telemetry sources
Batch and streaming data pipelines
Near-real-time data pipelines
Streaming
Distributed processing
Cloud-native architectures

Education / Licenses / Certifications

College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent experience required.
This position may require licensing for compliance with export controls or sanctions regulations.

Additional Responsibilities & Preferred Key Competencies

Experience designing enterprise-level analytical, operational, or domain data models across multiple manufacturing and supply-chain business functions and source systems.
Experience implementing metadata-driven pipelines, reusable ingestion frameworks, self-service data capabilities, data governance, lineage, observability, or reusable data-product patterns.
Experience with data architecture and engineering patterns supporting GenAI and RAG, including document ingestion and processing, embeddings, vector search/vector databases, semantic models, knowledge graphs, ontologies, or retrieval pipelines.
Experience with manufacturing and supply-chain technologies and data sources such as ERP/MRP, MES, PLM, WMS, TMS, planning systems, engineering systems, or IoT/connected-product platforms.
Ability to balance near-term business delivery with longer-term architecture, scalability, reuse, governance, cost optimization, and technical debt.
Relevant Databricks, Snowflake, Azure, AWS, GCP, or comparable data-platform certifications are a plus; production experience and technical depth are valued more than certification alone.

Relocation

Relocation package: Yes

Location: Columbus, IN (onsite) | Role category: On-site with Flexibility | Job type: Exempt - Experienced

Salary: USD 131,220 - 160,380 per yearly | Min salary: $131220 | Max salary: $160380 | REQID: 2438266

Note: Salary range estimate provided in good faith; final offer determined based on qualifications and experience, where appropriate.

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1mo ago

Senior IT Data Engineer

System One Washington, DC

Washington, DC

1mo ago Closed

Contract Senior Apache Airflow AWS

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

System One is hiring a Senior IT Data Engineer to support the Federal Reserve Board’s Division of Research & Statistics (R&S) DATA section in Washington, DC (onsite).

Responsibilities

Expand and optimize data and data pipeline architecture.
Optimize data flow and collection to support economic policy and research teams.
Design and develop optimal data delivery architecture.
Improve existing data systems and/or build new systems from the ground up.
Optimize or redesign the R&S division data architecture to support next generation data initiatives.
Support economists and technical experts.
Provide service-minded support for multiple teams and systems with a self-directed working approach.
Design and communicate enterprise information architecture across conceptual, logical, and physical levels.

Requirements

Bachelor’s degree in computer science, Information Technology, Engineering, or related technical field; at least 7 years of related experience (advanced degree preferred).
Advanced working knowledge of SQL.
Experience with relational database platforms including PostgreSQL, Microsoft SQL Server, and MySQL.
Advanced working knowledge of Python, R, and other scripting languages used for data engineering and analytics.
Experience with large-scale data systems: distributed computing, scalable data processing, data storage architecture, and optimization of high-volume data workloads.
Experience designing, developing, and automating ETL/ELT workflows and data integration pipelines.
Experience building, optimizing, and maintaining scalable databases, data pipelines, and data processing frameworks.
Experience with workflow orchestration and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.
Experience migrating workflows and data pipelines between on-premises and cloud environments.
Experience processing, analyzing, and integrating structured and unstructured data sources.
Experience developing in Linux and using source control platforms such as GitLab and/or GitHub.
Ability to perform root cause analysis on internal and external data and business processes to answer business questions and identify improvement opportunities.
Ability to design and communicate enterprise information architecture at conceptual, logical, and physical levels.
In-depth experience designing and implementing database, data lake, and enterprise data platform solutions.
Strong hands-on software engineering experience including development, testing, and deployment of data applications and services.
Excellent oral and written communication skills, with a strong customer service orientation.
Exceptional analytical, problem-solving, and troubleshooting skills.
Understanding of time series data and related analytical and forecasting techniques.
Experience working in a research environment and/or with economic or financial data.
Experience with NoSQL and graph database technologies.
Experience developing, training, deploying, and maintaining machine learning models.
Working experience with AWS, Microsoft Azure, and Snowflake.
Experience implementing data warehouses utilizing Change Data Capture (CDC) methodologies.
Experience implementing and maintaining CI/CD pipelines and DataOps platforms.
Working knowledge of additional programming and scripting languages such as Java, Scala, JavaScript, or Perl.

Technology Stack

SQL, PostgreSQL, Microsoft SQL Server, MySQL
Python, R
Apache Airflow, Prefect, Dagster, AWS Step Functions
Linux, GitLab, GitHub
NoSQL, graph database technologies
Machine learning models
AWS, Microsoft Azure, Snowflake
Change Data Capture (CDC)
CI/CD pipelines, DataOps
Java, Scala, JavaScript, Perl

Benefits

Eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans.
Participation in a 401(k) plan.

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1mo ago

Staff Data Engineer

Okta Washington, DC

Washington, DC

1mo ago Closed

$174k - $239k/yr Full time Cloud Architecture Data Architecture Data Engineer

This position is no longer accepting applications (closed Aug 25, 2026).

Job Description

Okta is seeking a Staff Data Engineer to steer the architectural evolution of the companys data platform, beginning with FEDRamp compliance. The role entails close collaboration across data, platform, and security groups to define and execute the architectural roadmap. This position is based in Washington, DC with a hybrid work arrangement and offers a salary range of USD 174,000 to 238,700 per year, requiring at least eight years of relevant software experience.

Responsibilities

Guide the ongoing design and evolution of the data platform, establishing a roadmap toward the target architecture.
Shape the technical strategy for large scale platform enhancements, balancing long term goals with incremental delivery.
Collaborate closely with engineers and leaders from data, platform, and security teams to craft a unified and secure architecture.
Produce architectural artifacts such as design documents, threat models, and technical specifications to provide clarity and alignment on complex initiatives.
Serve as a technical mentor and multiplier for the Data Engineering team, raising performance through guidance, code reviews, and dissemination of best practices.
Implement foundational components of the new architecture, validating designs with hands on coding and providing a model for peers to follow.

Requirements

A commitment to building secure, reliable, and scalable data systems.
8+ years of software development experience, with at least 5+ years in a data engineering or data platform role.
Proven experience delivering large scale, cross functional technical projects.
Extensive experience designing and deploying data infrastructure in a cloud environment, with AWS strongly preferred.
Deep architectural knowledge of the modern data stack, including data warehouses (Snowflake), transformation tools (dbt), and orchestrators (Airflow).
Strong proficiency in Python and SQL, with a high standard for code quality and system design.
Excellent communication skills, enabling clarity and decisions on complex technical topics.
Ability to navigate ambiguity, define a path forward, and lead others to successful outcomes.

Technologies

Snowflake
dbt
Airflow
Python
SQL
AWS
Terraform
Kubernetes
AWS GovCloud

Benefits

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

The Auth0 Data Engineering Team

Pipeline team, positioned near the Platform team and data producers, responsible for efficient data ingestion and providing rapid access to unmodeled data
Warehouse team, closer to business teams and data consumers, focused on modeling data in the data warehouse to simplify analysis, reporting, and decision making
Interface team, accountable for building and managing connections between the data platform and external systems, ensuring consistent and reliable data access

The Okta Experience

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

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2mo ago

Database Developer

SOUTHEASTERN COMP CONSULTANTS INC Dahlgren, VA

Dahlgren, VA

2mo ago Closed

Full time Senior Cloud Architecture Data Architecture

This position is no longer accepting applications (closed Aug 11, 2026).

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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2mo ago

Associate Director, Data Engineer: DSCS Digital Data Strategy

Merck Boston, MA

Boston, MA

2mo ago Closed

$129k - $203k/yr Full time Senior Analytics Associate Director

This position is no longer accepting applications (closed Jul 28, 2026).

Job Description

Merck is seeking an Associate Director, Data Engineer within the DSCS Digital Data Strategy team, based on site in Boston, MA. The role centers on designing, constructing, and governing biologics data pipelines while shaping an end-to-end data strategy to support modeling, optimization, and decision-making across Digital Insights. This position requires a PhD and at least three years of relevant experience, with a salary range of $129,000 to $203,100 per year.

Responsibilities

Own the biologics data engineering domain, maintaining broad awareness of digital projects, data sources, systems, and data flows within the domain.
Contribute to defining and guiding the DSCS Digital Data Strategy.
Design and implement robust, scalable data pipelines that ingest experimental and process data from biologics source systems including process historians, chromatography equipment, electronic lab notebooks, and analytical instruments.
Provide analysis-ready datasets to support digital initiatives, covering process characterization models, data lineage, multivariate analytics, and cross-site manufacturing connectivity.
Establish and enforce data standards, metadata schemas, and ontology mappings to ensure biologics data is interoperable and readily usable by modeling and optimization workflows.
Collaborate proactively with automation teams to anticipate when new or modified automated workflows generate new data streams requiring pipeline development and ontology mapping.
Own and govern system-of-record standards for biologics, ensuring consistent configuration and data entry across experiments, molecules, and sites.
Catalog processes, analytical methods, instruments, and digital systems within the biologics domain to create a comprehensive data-landscape map.
Create and maintain data visualizations, dashboards, and reports that enable scientists to explore process data across runs, molecules, scales, and manufacturing sites.
Contribute to the biologics digital data strategy by identifying opportunities to improve data capture at the source and reduce friction between experimentation and modeling.
Mentor and guide supporting data engineers across modalities, ensuring alignment with domain strategy and ontology governance.
Maintain and version pipeline code in GitHub, adhering to team standards for code review, documentation, and deployment.
Build strong partnerships with process development scientists, analytical scientists, and manufacturing teams to gather requirements and shape the domain's digital data strategy.
Demonstrate excellent interpersonal, communication, and collaboration skills.
Model and promote diversity and inclusion within the team, fostering a supportive culture where all can thrive.
Collaborate effectively in a dynamic, integrated, multidisciplinary environment.

Requirements

Proficiency in Python and/or R, with comfort using development environments such as Jupyter, Posit/RStudio, or VS Code.
Strong SQL skills with hands-on experience writing and optimizing queries for relational databases and data warehouses.
Experience building ETL/ELT pipelines in a scientific or pharmaceutical context.
Familiarity with cloud platforms (AWS, Azure, or GCP) for data storage, processing, and integration.
Working knowledge of how process models, multivariate analyses, and statistical tools rely on experimental data to anticipate modeler needs and deliver structured datasets.
Experience defining or enforcing data standards, metadata schemas, or ontology mappings in a scientific or pharmaceutical setting.
Familiarity with version control systems (Git/GitHub) and collaborative software development practices.
Proven ability to lead technical initiatives, mentor junior engineers, and influence data strategy across multiple stakeholders.
Ability to deliver complex solutions under compressed timelines in a dynamic environment.

Technologies

Python and R
Jupyter, Posit/RStudio, VS Code
SQL
AWS, Azure, GCP
Databricks, Delta Lake
Git, GitHub
Streamlit, Shiny
Power BI, Spotfire, Tableau
Allotrope Simple Model, ISA-88, OPC-UA

Benefits

Medical, dental, and vision coverage for you and your family
Retirement benefits including a 401(k) plan
Paid holidays and vacation time
Sick leave and compassionate time off
Annual bonus and potential long-term incentives where applicable

Preferred Experience and Skills

Hands-on biologics process development experience—such as chromatography, filtration, purification, or formulation—and a track record transitioning into data engineering, data science, or computational roles.
Experience with data pipelines and analytics platforms such as Databricks, including notebook-based development, workflow orchestration, and Delta Lake.
Proven ability to create scientist-facing dashboards and exploratory data applications using visualization tools (Streamlit, Shiny, Power BI, Spotfire, Tableau).
Familiarity with ontology frameworks or standardized data models (e.g., Allotrope Simple Model, ISA-88, OPC-UA) and data mapping from instruments to structured schemas.
Understanding of Design of Experiments and process characterization study designs to structure data for statistical analysis of CPPs and CQAs.
Experience implementing data lineage and traceability across experimental systems, materials, and manufacturing steps.
Knowledge of regulatory expectations relevant to biologics process development, characterization, and validation (ICH Q8-Q12, validation lifecycle, comparability studies).
Experience collaborating with lab automation teams to integrate data from newly automated workflows.
Experience with cross-site data integration and harmonizing data from multiple manufacturing facilities.
Evidence of cross-functional collaboration spanning laboratory, manufacturing, modeling, and digital teams.

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4mo ago

Tableau Developer

Qualit Resources, LLC Hartford, CT

Hartford, CT

4mo ago Closed

$45 - $52/hr Full time Analytics Business Analytics Business Intelligence

This position is no longer accepting applications (closed Jun 16, 2026).

Job Description

Qualit Resources, LLC seeks a Senior Tableau Developer to oversee Tableau report development, ETL and data integration, and data migration efforts for enterprise applications. This hybrid role is based near Hartford, Connecticut, with in-office requirements.

Responsibilities

Lead the design and development of Tableau reports to meet user needs.
Contribute to the design and development of the database architecture, including relational data structures, data marts, data dictionaries, and both logical and physical data models.
Create strategies for data acquisition, data quality, and discrepancy resolution.
Assist in migrating and integrating data and processes from legacy systems to modern applications and technologies.
Develop and maintain efficient, well documented custom SQL scripts, stored procedures, and triggers using Microsoft T-SQL to support application development in alignment with business rules.
Access data across multiple database management systems such as DB2, SQL Server, and others.
Design, develop, and implement ETL/ELT solutions for data ingestion, cleansing, business rules execution, and data distribution.
Apply data analytics best practices in data modeling, ETL pipelines, and near real-time data solutions.
Coordinate with Business Analysts and users to validate requirements.
Implement solutions to integrate external data with in-house data.
Test and validate data flows and prepare ETL processes according to business requirements.
Design and implement a data conversion strategy from legacy platforms to new ones.
Perform design validation, reconciliation, and error handling in data load processes.
Optimize SSIS package execution and SQL execution to improve data load performance.
Design SSIS packages using data exchange tasks such as File Transfer and Secured File Transfer, with FTP/SFTP import/export capabilities.
Engage in all project phases, including requirements gathering, data mapping, extraction, loading, testing, troubleshooting, documentation, performance optimization, and maintenance.
Develop various Tableau reports per user requirements and deploy to report servers or integrated SharePoint report server.
Utilize dynamic grouping fields, dynamic group sorting, on-demand subreports, drill-down and summary reports, and cross tab reports to highlight key summary information.

Requirements

More than five years of experience with Tableau.
More than five years of experience writing complex SQL queries.
More than five years of expertise with T-SQL, SSRS, SSIS or Talend.
Experience debugging and improving query performance.
Experience deploying SSIS packages using Git check-ins, configuring environmental variables, and creating corresponding SQL Agent jobs.
Experience with Transact-SQL and stored procedures is desirable.
Experience creating, deploying, and maintaining Talend reports.
Experience with code control and versioning using Team Foundation.
Strong problem solving, cross-functional analysis, and forward-thinking abilities.
Flexibility to adapt to changing situations, handle multiple tasks, and meet tight deadlines.

Technologies

Tableau
SSIS
SSRS
T-SQL
Transact-SQL
SQL Server
DB2
Talend
Git
Team Foundation
SharePoint
FTP
SFTP
SQL Agent

Additional Preferred Qualifications

Experience with Salesforce
MuleSoft

Pay

Compensation: USD 45.00 to 52.00 per hour.

Work Location

Hybrid remote in Hartford, CT 06144.

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Data Strategy Developer Jobs

Data Engineer Principal

Senior IT Data Engineer

Staff Data Engineer

Database Developer

Associate Director, Data Engineer: DSCS Digital Data Strategy

Tableau Developer

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