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Today

Senior, Data Engineer

Epsilon Chicago, IL

Chicago, IL

Today

$146k - $182k/yr Full time Python Senior Amazon Web Services

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Job Description

Epsilon is seeking a Senior Data Engineer (Employer: Epsilon Data Management LLC) to build and optimize AWS and Greenplum data pipelines that support internal data products. The role focuses on end-to-end delivery, from SQL and Python development through testing, monitoring, and data governance, with an emphasis on secure, scalable processing at scale.

This position is based in Chicago, IL (hybrid), with required in-office attendance certain days per week and telecommuting for the rest of the week.

What you’ll do

Develop and execute software tests to surface software problems and identify root causes.
Write and optimize complex SQL scripts and build Python scripts to run large-scale transformations on Greenplum.
Create test plans, run unit and integration tests, and deliver reproducible, well-documented results.
Design and maintain AI-enabled PySpark pipelines on AWS, primarily using EMR, Glue, Athena, DynamoDB, and S3 to process large datasets.
Harden and tune jobs for performance, cost, and compliance, including managing data partitioning, cataloging, and lineage.
Automate deployments and infrastructure using CloudFormation and parameterized configurations, and schedule batch workloads for timely, reliable pipelines.
Build internal dashboards and data products (including Amplify apps) and implement monitoring and alerting to detect issues early.
Handle client tickets by translating ambiguous requests into clear technical tasks.

What you bring

A Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
2+ years of experience in the job offered, or 2 years in any occupation where the required experience was gained (employer will accept the specified combination of education and experience).
Experience building PySpark ETL on AWS using EMR/Glue with S3, including partitioning, predicate pushdown, and broadcast joins to produce analytics-ready fact/dimension tables on schedule.
Ability to author and tune complex SQL on Greenplum/Postgres, including window functions and ROW_NUMBER dedupe, plus physical design and maintenance approaches such as distribution keys, AO/AOCO compression, and VACUUM/ANALYZE.
Experience managing AWS Glue Data Catalog and curated layers with Athena, designing S3 layouts (prefix/partition strategy and lifecycle policies) to reduce query time and storage cost.
Hands-on CI/CD using CodeCommit, CodeBuild, and CodePipeline, plus parameterized environments and CloudFormation-based infrastructure as code for repeatable, auditable rollbacks.
Observability engineering with CloudWatch logs/metrics/alarms, job health checks, SLA dashboards, and alerting to detect failures early and reduce MTTR.
Data quality enforcement through SQL/Python unit tests, reconciliation (row counts, sums, duplicates), referential integrity checks, and documented UAT evidence for change control.
Security and governance experience, including normalizing and encrypting sensitive identifiers, using KMS-managed keys, and applying IAM least privilege with audit logging.
Experience delivering GenAI-assisted features by integrating LLMs (using AWS Bedrock) with PySpark/SQL to suggest transformations, generate test cases, and summarize validation results.
Experience building lightweight internal data apps using AWS Amplify with DynamoDB/Athena to manage lookup keys/brand lists and enable stakeholder self-service with controlled access.

Tools and technologies

SQL, Python, Greenplum, PySpark
AWS EMR, AWS Glue, AWS Athena, Amazon DynamoDB, Amazon S3
CloudFormation, AWS CodeCommit, AWS CodeBuild, AWS CodePipeline
Amazon CloudWatch, AWS KMS, AWS IAM
AWS Bedrock, AWS Amplify, Postgres

Compensation

USD $145,870 - $182,000 per year.

Benefits

Flexible time off (FTO), 14 paid holidays, paid sick time
Parental/new child leave, childcare & elder care assistance, adoption assistance
Comprehensive health coverage
401(k)
Tuition assistance
Commuter benefits
Professional development
Employee recognition
Charitable donation matching
Health coaching and counseling

Location

35 West Wacker Drive, Chicago, IL 60601

Required to work from the company office in Chicago, IL certain days per week. Telecommuting is allowed for the balance of the week.

About Epsilon

Epsilon is a global leader in data and identity, with deep expertise in digital media, clean rooms, customer data platforms, loyalty and marketing services. Epsilon operates in 30+ countries across EMEA, the Americas, and APAC, with more than 8,000 employees.

Epsilon’s values include Act with integrity, Work together to win together, Innovate with purpose, Respect all voices, and Empower with accountability.

Equal opportunity and accommodations

Epsilon is an equal opportunity employer and does not discriminate based on protected categories.
Accommodations are available for applicants who need help completing the application process. Contact LeaveofAbsence@epsilon.com to request an accommodation.
In the San Francisco Bay and Los Angeles areas, Epsilon will consider qualified applicants with criminal histories in a manner consistent with applicable fair chance ordinances.

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1d ago

Data Engineer

iHeartMedia, Inc. San Antonio, TX

San Antonio, TX

1d ago

Full time Amazon Web Services Apache Airflow AWS

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Job Description

The Data Engineer role at iHeartMedia, Inc. reports to the Director of Software Engineering and focuses on delivering dependable, production-ready data solutions. You will partner with data scientists and business stakeholders to build data pipelines, infrastructure on AWS, and supporting services for analytics and model workflows.

Responsibilities

Develop, test, deploy, and maintain data solutions aligned to business requirements, web applications, models, and analytics.
Collaborate with data scientists, analysts, product teams, and business stakeholders to gather requirements and deliver reliable data solutions.
Design, build, and maintain data pipelines and ETL/ELT workflows using PySpark, AWS Glue, Pandas, and orchestration tools such as Apache Airflow or AWS Step Functions.
Implement data ingestion, transformation, validation, storage, and pipeline monitoring.
Build infrastructure to support model training, scoring, retraining, and associated reporting.
Deploy and manage applications and pipelines using AWS CodePipeline and ECS.
Monitor data quality, troubleshoot issues, and optimize pipeline performance.
Work with a small, agile team and resolve technical problems through debugging and troubleshooting.

Requirements

6+ years of professional experience in data engineering.
Experience building high-performance applications for large enterprises.
Hands-on AWS cloud experience (or a similar cloud platform), including Glue, CodePipeline, and ECS.
Strong proficiency in Python (including PySpark, Pandas, and DataFrames) and SQL.
Experience designing, developing, and maintaining data pipelines using AWS Glue or similar technologies.
Experience building and managing ETL/ELT workflows using Apache Airflow, AWS Step Functions, or comparable orchestration tools.
Understanding of core data engineering concepts: ingestion, transformation, validation, storage, and pipeline monitoring.
Familiarity with data quality monitoring, troubleshooting, and performance optimization.
Database experience with Postgres, MongoDB, DynamoDB, and Athena.
Experience with Git and collaborative software development practices.
Experience using agile development methodologies.
Proven ability to meet project timelines with a sense of urgency.

Technologies

PySpark, AWS Glue, Pandas
Apache Airflow, AWS Step Functions
Python, SQL
AWS CodePipeline, ECS
Postgres, MongoDB, DynamoDB, Athena
Git
AWS SageMaker, Apache Iceberg, Delta tables

Preferred

Experience with AWS SageMaker or similar ML platforms.
Knowledge of Apache Iceberg and Delta tables.

Benefits

Employer sponsored medical, dental, and vision with a variety of coverage options.
Company provided and supplemental life insurance (pursuant to the collective bargaining agreement if applicable).
Paid vacation and sick time.
Paid company holidays.
A Spirit day to encourage and allow employees to more easily volunteer in their community.
A 401K plan.
Employee Assistance Program (EAP) at no cost, including telephonic counseling sessions and consultation on legal and financial matters, emotional well-being, and family and caregiving.
Additional voluntary programs, such as spending accounts, student loan refinancing, accident insurance, and more.

Location and Employment Details

San Antonio, TX (onsite): 20880 Stone Oak Parkway, 78258.

Position type: Regular
Time type: Full time
Pay type: Salaried

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1d ago

Analyst, Data Engineer

Firehouse Subs Jacksonville, FL

Jacksonville, FL

1d ago

Full time Amazon Web Services Analytics AWS

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Job Description

In this onsite role in Jacksonville, FL, you will build reliable data workflows that support analytics, governance, and machine learning initiatives.

Responsibilities

Design, build, and maintain data pipelines and ETL processes to enable smooth data movement.
Develop and maintain scalable data warehouse solutions aligned with expanding organizational reporting and data needs.
Monitor and troubleshoot pipelines; identify issues and help drive timely resolution.
Model data tables and create business intelligence reporting dashboards.
Support the team’s data engineering strategy and ensure work aligns with organizational goals.
Collaborate with the team and manager to evaluate and adopt new technologies and methodologies to improve data engineering capabilities.

Requirements

1+ years of hands-on experience in data engineering, data analytics, or a related technical field.
Bachelor’s degree in computer science, engineering, or related field, or equivalent experience.
Experience with AWS, including services such as S3, Glue/EMR, SQS, and Step Functions.
Strong programming skills in SQL and Python.
Experience querying and building in Snowflake using dbt.
Familiarity with version control, continuous integration, and infrastructure as code.
Familiarity with business intelligence reporting tools.
Knowledge of Point of Sale and Back of House systems is helpful.
Strong problem-solving and analytical skills.
Clear communication skills and ability to work with cross-functional teams.

Technology

AWS (S3, Glue, EMR, SQS, Step Functions)
SQL, Python
Snowflake, dbt

Benefits

Comprehensive global paid parental leave program
Free telemedicine
Mental wellness support

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2d ago

Data Engineer

Amazon Data Services, Inc. Austin, TX

Austin, TX

2d ago

$132k - $179k/yr Full time 3d Design Tools Amazon Web Services AWS

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Job Description

This Data Engineer role supports AWS MOTOR within the Supply Chain Intelligence team, focused on building data infrastructure and pipelines that enable reliable, actionable insights for operational stakeholders.

Role Overview

Working in the Supply Chain Intelligence team, you will build and lead data infrastructure across the supply chain to deliver clean data and dependable analytics outcomes. The work spans manufacturing operations, transportation operations, and reverse processes, with an emphasis on operational excellence and data that is ready for use by analytics and science partners.

Responsibilities

Build and maintain data infrastructure that supports data-driven question answering, applying software engineering best practices, data management fundamentals, data storage principles, advances in distributed systems, and operational excellence practices.
Create and support datasets used by analysts and scientists to produce actionable insights.
Define data engineering processes that use AWS services to improve accessibility, redundancy, data integrity, and cost and storage effectiveness.
Develop scalable solutions that support faster delivery of products and models aligned to business needs, while accounting for future requirements.
Partner with Research/Applied Scientists, Data Engineers, Business Intelligence Engineers, Data Scientists, Business Analysts, and Product/Program Managers to clarify requirements and make technical decisions that support smoother execution.
Interface with other technology and data engineering teams to extract, transform, and load data from a variety of sources using AWS data technologies.
Lead technical design and implementation efforts for the data infrastructure.
Design and manage data audit, quality, and reconciliation processes in collaboration with relevant stakeholders.

Required Qualifications

3+ years of data engineering experience
Experience with data modeling, warehousing, and building ETL pipelines

Preferred Qualifications

Experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases and data stores such as object storage, document or key-value stores, graph databases, and column-family databases

Technologies

AWS services and related components, including Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM, plus object storage, document stores, key-value stores, graph databases, and column-family databases.

Team and Mission

This team provides data engineering and business intelligence engineering services to the rest of MOTOR. The group acts as data experts behind the scenes, helping operational teams focus on operations by ensuring accurate and timely data and by delivering business insights that support operational excellence.

Compensation and Location

Location: Austin, TX (onsite)
Salary: USD 132,100 - 178,800 per yearly

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave

Learn more about benefits at https://amazon.jobs/en/benefits.

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2d ago

Lead Data Engineer

Bartech Staffing Charlotte, NC

Charlotte, NC

2d ago

Full time Backend Developer Manager Amazon Web Services

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Job Description

Bartech Staffing is hiring a Lead Data Engineer for a hybrid role based in Charlotte, North Carolina, with Charlotte preferred. In this position, you will lead the design and delivery of enterprise data engineering solutions across the AWS ecosystem, providing technical direction and hands-on mentorship to build reliable, scalable platforms.

What You Will Do

Own the design, architecture, and implementation of enterprise data engineering solutions across AWS
Partner with Lead Developers, Data Scientists, Architects, Product Owners, and business stakeholders to define technical strategy and scalable solutions
Provide technical leadership and mentorship to Data Engineers and development teams, promoting best practices and engineering excellence
Drive key architectural decisions with Data Architects and Solution Architects to support scalability, security, reliability, and maintainability
Design and oversee data warehouse and data lake solutions that balance usability, performance, and long-term sustainability
Establish engineering standards for data modeling, ETL frameworks, pipeline reliability, monitoring, and operational excellence
Lead end-to-end solution delivery, ensuring alignment with business requirements, enterprise architecture standards, and regulatory requirements
Oversee production support and operational management of AWS-based data platforms, including root-cause analysis and performance optimization
Champion data quality, governance, observability, and data stewardship practices across platforms and teams
Find opportunities to modernize data architecture and improve operational efficiency through automation and cloud-native technologies

Core Requirements

8+ years of Data Engineering experience, including 5+ years working extensively within AWS ecosystems
Expert knowledge of AWS services including S3, EMR, Glue Jobs, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, and Step Functions
Experience creating AI applications with AWS Bedrock
Strong experience building enterprise-scale data lake and data warehouse solutions using Lake Formation, Amazon Redshift, and Amazon Athena
Extensive experience with Kafka-based streaming architectures, preferably Confluent Kafka
Advanced SQL and data modeling expertise, including dimensional modeling and data vault approaches for large-scale warehousing
Deep experience designing, developing, and optimizing scalable, resilient data pipelines in AWS environments
Strong understanding of distributed data processing frameworks, particularly PySpark and EMR
Expertise in database management principles, performance tuning, and data architecture best practices
Advanced Python development skills with hands-on experience using PySpark
Expertise in Infrastructure as Code using Terraform
Experience designing and implementing CI/CD frameworks using GitHub and GitHub Actions
Deep knowledge of AWS IAM roles, policies, governance, and security best practices
Experience with workflow orchestration tools such as AWS Step Functions, Apache Airflow, or equivalent platforms
Experience leading cloud migration, modernization, and enterprise data platform initiatives
Strong understanding of data governance, metadata management, data quality frameworks, and observability principles
Ability to lead hands-on development while providing technical direction, code reviews, and engineering oversight across multiple initiatives
Experience establishing development environments, infrastructure standards, security controls, and migration strategies across multiple AWS accounts and environments
Ability to architect, develop, and govern enterprise-scale data pipelines, ETL processes, ingestion frameworks, and orchestration workflows
Proven ability to identify data gaps, define strategic remediation plans, and implement scalable automation solutions that improve analytical capabilities
Ability to design and implement highly reliable data pipelines with strong focus on data quality, observability, resiliency, and operational supportability
Experience building and optimizing large-scale data warehousing solutions with attention to business user experience and system performance
Ability to influence architectural direction, drive technical decisions, and communicate complex concepts to technical and non-technical stakeholders
Proven track record mentoring engineers, fostering technical growth, and building high-performing data engineering teams
Experience leading cross-functional initiatives across data engineering, analytics, architecture, platform engineering, and business stakeholders
Strong problem-solving and leadership skills, with the ability to manage competing priorities in fast-paced enterprise environments
Experience building AI-ready data pipelines and ML workflows, including feature engineering and MLOps
Proficiency in Python, SQL, Spark, and Generative AI technologies for scalable data and analytics solutions
Hands-on experience with AWS, Azure, or Databricks and cloud-based AI/data platforms
Knowledge of LLMs, RAG, and vector databases to support AI-powered applications and intelligent search
Strong understanding of data governance, quality, security, and responsible AI practices

Technologies You Will Work With

AWS, S3, EMR, Glue Jobs, Lambda, Athena, CloudTrail, SNS, SQS, CloudWatch, Step Functions
AWS Bedrock, Lake Formation, Amazon Redshift, Kafka, Confluent Kafka
SQL, dimensional modeling, data vault, PySpark, Python, Terraform
GitHub, GitHub Actions, AWS IAM, Apache Airflow, ETL, CI/CD
Generative AI, Azure, Databricks, LLMs, RAG, vector databases, MLOps, Spark

Preferred Qualifications

AWS Certified Data Engineer, AWS Solutions Architect, or equivalent cloud certifications
Experience implementing enterprise data governance and metadata management platforms
Experience with real-time analytics, event-driven architectures, and streaming data platforms
Knowledge of modern data architecture patterns including Data Mesh, Lakehouse, and domain-oriented design
Experience leading large-scale cloud transformation or enterprise data modernization programs

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2d ago

Lead Software Engineer - Data Engineer

JPMorganChase Atlanta, GA

Atlanta, GA

2d ago

Full time Backend Developer 3d Design Tools Amazon Web Services

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Job Description

The Lead Software Engineer - Data Engineer will join JPMorgan Chase within the Cloud Financial Management Technology group, contributing as a core technical member on an agile team. This role emphasizes trusted delivery of secure, stable, and scalable technology products, with an added focus on secure, AI-assisted engineering practices and production data pipeline development on AWS.

Responsibilities

Deliver creative software solutions across design, development, and technical troubleshooting, applying the ability to think beyond routine approaches when solving complex problems.
Write secure, high-quality production code and perform reviews and debugging for code produced by others.
Drive enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, including AI-assisted code review and refactoring, test strategy acceleration, and incident and root-cause analysis support.
Establish consistent validation standards across the team, including secure coding, peer review, and automated testing, while promoting reuse of proven patterns.
Apply knowledge of Software Development Life Cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to increase value from automation.
Identify recurring remediation opportunities and work to eliminate or automate them to improve operational stability across software applications and systems.
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and fit for existing systems and information architecture.
Lead communities of practice across Software Engineering to increase awareness and adoption of new and leading-edge technologies.
Support a team culture focused on diversity, opportunity, inclusion, and respect.

Requirements

Formal training or certification on software engineering concepts, plus 5+ years of applied experience.
Proficiency in system design, testing, and operational ownership.
Advanced Python experience and cloud-native engineering on AWS, including IAM, VPC, KMS, and CloudWatch.
Demonstrated production delivery of ETL/ELT pipelines (batch and/or streaming) on AWS using services such as AWS Glue, Amazon EMR, AWS Lambda, and orchestration via Amazon MWAA (Airflow) and/or AWS Step Functions.
Strong data engineering fundamentals including CDC/incremental processing, backfills, idempotency, late-arriving data handling, and schema evolution.
Experience building on AWS analytics and storage services such as Amazon S3, Amazon Redshift, Amazon Athena, and AWS Lake Formation/Glue Data Catalog, along with streaming and messaging systems including Amazon Kinesis and Amazon MSK.
Data reliability experience covering data quality controls, monitoring and alerting, and CI/CD for pipelines (for example CodePipeline/CodeBuild), with performance and cost optimization and security and governance compliance (for example CloudTrail and least-privilege access).
Proven experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting, including the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Knowledge of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations, plus experience coaching engineers on safe and compliant adoption.
Practical experience using Large Language Models (LLMs) to accelerate advanced coding workflows.

Required Technologies

Python, AWS, IAM, VPC, KMS, CloudWatch
AWS Glue, Amazon EMR, AWS Lambda
Amazon MWAA (Airflow), AWS Step Functions
CDC/incremental processing, Amazon S3, Amazon Redshift, Amazon Athena
AWS Lake Formation/Glue Data Catalog, Amazon Kinesis, Amazon MSK
CodePipeline, CodeBuild, CloudTrail
Large Language Models (LLMs)

About the Team

JPMorgan Chase professionals in Corporate Functions support a wide range of areas, including finance and risk, human resources, and marketing. These corporate teams help ensure the organization is positioned for success across its businesses, clients, customers, and employees.

Location

Atlanta, GA (onsite)

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2d ago

Data Engineer II, Product BI

Amazon Development Center U.S., Inc. Seattle, WA

Seattle, WA

2d ago

$132k - $179k/yr Full time 3d Design Tools Amazon Ec2 Amazon Web Services

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Job Description

The Data Engineer II, Product BI role at Amazon Development Center U.S., Inc. focuses on creating scalable, compliant data products and business intelligence analytics that support AWS product innovations. The position emphasizes ETL/ELT workflows, OLAP technologies, data modeling, and SQL.

Role Responsibilities

Build scalable solutions to address ever growing data needs while staying compliant and adapting to diverse business requirements
Create data products designed to simplify customer problems and improve operational and technical efficiency
Develop and operate large-scale data structures for business intelligence analytics using ETL/ELT
Develop and operate large-scale data structures for business intelligence analytics using OLAP technologies
Develop and operate large-scale data structures for business intelligence analytics using data modeling
Develop and operate large-scale data structures for business intelligence analytics using SQL
Develop and operate large-scale data structures for business intelligence analytics using Oracle

Required Qualifications

5+ years of data engineering experience
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using OLAP technologies
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using data modeling
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using SQL
3+ years of experience developing and operating large-scale data structures for business intelligence analytics using Oracle
Experience with data modeling, data warehousing, and building ETL pipelines

Technologies

Work includes services and tools such as Amazon Elastic Compute Cloud (EC2), Redshift Serverless, Containers (ECS, EKS), streaming services, ETL/ELT, OLAP, SQL, Oracle, data modeling, warehousing, Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions. Additional data platforms referenced include object storage, document or key-value stores, and graph databases, along with column-family databases.

Preferred Qualifications

Experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases/data stores such as object storage, document or key-value stores, graph databases, and column-family databases

Location and Compensation

Seattle, WA (onsite). Salary range: USD 132,100 - 178,800 per year.

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, plus option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts)
Adoption and Surrogacy Reimbursement coverage
401(k) matching
Paid time off
Parental leave

About the Team

The team delivers product innovations built on foundational services including Amazon EC2, Redshift Serverless, Containers (ECS, EKS), and other streaming services to support ongoing releases and data-driven insights. The role supports a customer-obsessed approach and focuses on building innovation through scalable data products.