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Data Engineer

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices.

From the employer’s posting
The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time. You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices. Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following responsibilities:

What you’ll bring

All qualifications

Core experience

  • Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
  • Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
  • Experience with designing and implementing real-time pipelines
  • Experience with data quality and validation
  • Experience with API design
  • SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.

Preferred experience

  • Experience with Databricks notebook workflows
  • 18 paid volunteer hours each year to make a difference in your community
  • Experience with Terraform
Qualification wording
Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
Experience with designing and implementing real-time pipelines
Experience with data quality and validation
Experience with API design
SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.
Experience with Databricks notebook workflows
18 paid volunteer hours each year to make a difference in your community
Experience with Terraform
Education & alternatives
Basic Qualifications: - Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline - A minimum of 5 years of experience in the data engineering and software development life cycle. Including:
Apply at FCA Group

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 2026today
Recorded sightings
2
Last seen by us
Nov 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,163 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 54.

From 11,335 similar postings that came down. Coming down is not always a hire.

FCA Group is hiring

7 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • Rust
  • Scala
  • SQL
  • AWS
  • Azure
  • BigQuery
  • Databricks
  • Delta Lake
  • GCP
  • Iceberg
  • Kafka
  • NoSQL
  • S3
  • Spark
  • Terraform
  • Airflow
  • Luigi
Where the posting names them
- A minimum of 4 years of hands-on experience working with AWS cloud services - Comprehensive experience with one or more programming languages such as Python, Java, or Rust - Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.)
- Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming). - Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment. - SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning.
- Stream Processing: Experience with Apache Flink for low-latency stream processing. - Scripting: Proficiency in Python for automation, data analysis, or scripting. - Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks).
- Experience with API design - Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming). - Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment.
- Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment. - SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning. - DevOps & Tools: Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines.
- A minimum of 4 years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores. - A minimum of 4 years of hands-on experience working with AWS cloud services - Comprehensive experience with one or more programming languages such as Python, Java, or Rust
- Comprehensive experience with one or more programming languages such as Python, Java, or Rust - Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.) - Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more
- Scripting: Proficiency in Python for automation, data analysis, or scripting. - Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks). - Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases.
- Comprehensive experience designing, implementing, and iterating data pipelines using Big Data technologies - Certification in AWS or other cloud providers - Experience with Databricks notebook workflows
- Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more - Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.) - Experience with designing and implementing real-time pipelines
- Certification in AWS or other cloud providers - Experience with Databricks notebook workflows - Experience with Terraform
- Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks). - Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases. Preferred Qualifications:
- Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.) - Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more - Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.)
Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following responsibilities: - Pipeline Development: Design and implement complex data processing pipelines using Apache Spark. - Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing.
- Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing. - Infrastructure as Code: Manage and provision cloud infrastructure using Terraform. - CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment.
- SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning. - DevOps & Tools: Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines. - Software Engineering Foundation: Solid understanding of data structures, algorithms, and design patterns. Experience applying "Clean Code" principles to data engineering.
- Experience with Databricks notebook workflows - Experience with Terraform Our Benefits — Designed with You in Mind

Your next step

Complete your application on careers.stellantis.com. The employer’s form will show what is required.

Already applied? Track this application

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,082.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

The AI & Data Analytics Team is looking for a Senior Data Engineer to join our team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that process massive datasets in both batch and real-time. You will work at the intersection of software engineering and data science, ensuring that our data architecture is scalable, reliable, and follows industry best practices. 

 

Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to, the following responsibilities: 

 

  • Pipeline Development: Design and implement complex data processing pipelines using Apache Spark. 
  • Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale batch processing. 
  • Infrastructure as Code: Manage and provision cloud infrastructure using Terraform. 
  • CI/CD & Automation: Streamline development workflows by implementing and maintaining GitHub Actions for automated testing and deployment. 
  • Code Quality: Uphold rigorous software engineering standards, including comprehensive unit/integration testing, code reviews, and maintainable documentation. 
  • Collaboration: Work closely with stakeholders to translate business requirements into technical specifications. 

Basic Qualifications: 

  • Bachelors degree in Computer Science, Engineering, Mathematics, or a related technical discipline  
  • A minimum of 5 years of experience in the data engineering and software development life cycle. Including:
    • A minimum of 4 years of hands-on experience in building and maintaining production data applications, current experience in both relational and columnar data stores. 
    • A minimum of 4 years of hands-on experience working with AWS cloud services  
  • Comprehensive experience with one or more programming languages such as Python, Java, or Rust 
  • Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS S3, etc.) 
  • Familiarity with time series database, data streaming applications, event driven architectures, Kafka, Flink, and more 
  • Experience with workflow management engines (i.e., Airflow, Luigi, Azure Data Factory, etc.) 
  • Experience with designing and implementing real-time pipelines 
  • Experience with data quality and validation 
  • Experience with API design 
  • Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming). 
  • Programming Mastery: Strong proficiency in Scala or Java. You should be comfortable building production-grade applications in a JVM-based environment. 
  • SQL Proficiency: Advanced knowledge of SQL for data transformation, analysis, and performance tuning. 
  • DevOps & Tools: Hands-on experience with Terraform for infrastructure management and GitHub Actions for CI/CD pipelines. 
  • Software Engineering Foundation: Solid understanding of data structures, algorithms, and design patterns. Experience applying "Clean Code" principles to data engineering. 
  • Stream Processing: Experience with Apache Flink for low-latency stream processing. 
  • Scripting: Proficiency in Python for automation, data analysis, or scripting. 
  • Cloud Platforms: Experience with AWS, Azure, or GCP data services (e.g., EMR, Glue, Databricks). 
  • Data Modeling: Familiarity with dimensional modeling, Lakehouse architectures (Delta Lake, Iceberg), or NoSQL databases.  

 

Preferred Qualifications:

  • Comprehensive knowledge of relational database concepts, including data architecture, operational data stores, Interface processes, multidimensional modeling, master data management, and data manipulation 
  • Expert knowledge and experience with custom ETL design, implementation and maintenance 
  • Comprehensive experience designing, implementing, and iterating data pipelines using Big Data technologies  
  • Certification in AWS or other cloud providers  
  • Experience with Databricks notebook workflows  
  • Experience with Terraform  

Our Benefits — Designed with You in Mind

Comprehensive Health & Well-being Coverage
From your very first day, you'll have access to medical, dental, vision, and prescription drug coverage — ensuring you and your family stay healthy and protected.

Generous Paid Time Off
We believe in work-life balance. That's why we offer: 17+ paid holidays, including shut-down from December 24th through New Years Day every year. Vacation, float & wellbeing days, sick time and fully paid parental leave when your family needs you most.

Competitive Retirement Savings Plans
We help you plan for the future with:

  • An employer match on contributions to your 401k, Roth, and Catch-Up plans
  • An employer contribution, even if you don't contribute

Income Protection & Insurance Options
Benefit from included and optional disability, life, and other insurance programs — because your peace of mind matters.

Company Vehicle Lease Program
Eligible employees and their immediate families can enjoy company vehicle lease options with included insurance, maintenance, and unlimited mileage. Plus, take advantage of exclusive discounts on Stellantis products.

Family Building Benefit
We proudly support all paths to parenthood- including fertility and infertility treatments, adoption services, and gestational surrogacy.

Support for Your Growth and Giving Back
We believe in investing in your future and your passions:

  • Tuition reimbursement
  • Student loan refinancing programs
  • 18 paid volunteer hours each year to make a difference in your community

And so much more!
When you join us, you're not just building a career — you're joining a company that supports you, inside and outside of work.

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Auburn Hills, MI, US

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