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Sr Data Engineer Jobs in Rochester, MI (NOW HIRING)

Next Step Systems

Data Architect

Farmington Hills, MI · On-site

$62.75 - $80.75/hr

Senior Data Modeler, Technical Lead, and Data Architect. - Participate and provide technical ... Developers and Technical Project Managers. - Learn new things, and grow rapidly from constant ...

Stefanini, Inc

Sr Software Engineer

Southfield, MI · On-site

$112K - $148K/yr

Job Details SoftwareEngineer Sr Software Engineer Southfield,MI Posted:8/5/2026 Job ID#: 64553 Job ... Plan, design, build, and maintain scalable data solutions including data pipelines, data models ...

Deloitte

Lead Forward Deployed Engineer - AWS

Detroit, MI · On-site

$101K - $133K/yr

Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

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All JobsSr Data Engineer JobsSr Data Engineer Jobs in Rochester, MI

Sr Data Engineer information

See Rochester, MI salary details

$74.6K

$116.3K

$161.1K

How much do sr data engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for sr data engineer in Rochester, MI is $116,279.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $132,500.00 per year, depending on experience, location, and employer.

What is a Sr data engineer?

Sr Data Engineers, or Senior Data Engineers, are experienced professionals responsible for designing, building, and maintaining scalable data pipelines and architectures. They work with large datasets, ensuring data quality, reliability, and accessibility for analytics and business intelligence purposes. Sr Data Engineers collaborate with data scientists, analysts, and other stakeholders to implement data solutions that support decision-making and business growth. Their expertise often includes proficiency in programming languages like Python or Java, experience with big data tools such as Hadoop or Spark, and a deep understanding of database systems.

How do Sr data engineers typically collaborate with data scientists and analysts within a project team?

Sr Data Engineers play a crucial role in bridging the gap between raw data and actionable insights. They work closely with data scientists and analysts to understand data requirements, design robust data pipelines, and ensure the reliability and scalability of data infrastructure. Regular collaboration involves translating analytical needs into technical specifications, optimizing data flow, and troubleshooting data issues. This teamwork ensures that data-driven projects progress smoothly and that the analytical team has timely access to clean, well-structured data.

What are the key skills and qualifications needed to thrive as a Sr data engineer, and why are they important?

To thrive as a Sr Data Engineer, you need expertise in data architecture, ETL processes, programming (such as Python or Scala), and a strong background in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, cloud platforms (AWS, Azure, GCP), and database management systems, along with relevant certifications, is typically required. Advanced problem-solving abilities, attention to detail, and strong collaboration skills help set top performers apart in this role. These skills and qualities ensure the efficient design, implementation, and maintenance of robust data pipelines that enable data-driven decision-making across the organization.

What is the difference between Sr Data Engineer vs Data Engineer?

AspectSr Data EngineerData Engineer
Required CredentialsBachelor's degree in CS or related field; 3+ years experience; SQL, Python, SparkBachelor's degree in CS or related field; 1-3 years experience; SQL, Python, Spark
Work EnvironmentCollaborates with data scientists, analysts; designs scalable data pipelinesBuilds and maintains data pipelines; supports data analysis
Employer & Industry UsageTech companies, finance, healthcare; used for complex data projectsStartups, enterprises; used for data collection and processing

The main difference between a Sr Data Engineer and a Data Engineer lies in experience level, responsibilities, and complexity of projects. Sr Data Engineers typically have more experience, handle more complex data architecture, and mentor junior staff, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but the senior role involves greater technical leadership and strategic planning.

What are popular job titles related to Sr Data Engineer jobs in Rochester, MI?

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Sr Data Engineer jobs near you
Infographic showing various Sr Data Engineer job openings in Rochester, MI as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $116,279 per year, or $55.9 per hour.

Data Scientist, HC Analytics

Detroit, MI • On-site

Henry Ford Health System
51 - 200 employees
Learn more about Henry Ford Health Systemexternal

Full-time

Posted 29 days ago

Job description

GENERAL SUMMARY: 

The Data Scientist, Healthcare Analytics assists the Senior Data Scientist, Healthcare Analytics and other business analysts with working with business users to fully understand their needs for data science solutions. Works with a variety of data sources, both internal and external, big and small, structured and unstructured formats to build analytic models utilizing machine-learning techniques. Partners with the IT group to ensure that the data is sourced from the right location for data science model building. Participates in the development of project deliverables, especially documentation, for data science deliverables. As a team player, interacts with various other roles such as data engineers, business analysts and others. The Data Scientist, Healthcare Analytics solves analytical problems and develops cutting edge solutions to business problems. Should also be skilled at extracting, transforming, and analyzing data using a variety of common analytical tools and statistical techniques. Should be able to present findings in a compelling manner to both a business and non-technical audience. The position requires a team player that is eager to continue to learn and evolve with business needs and changes in the data and business environment. 

EDUCATION/EXPERIENCE REQUIRED: 

  • Must have an undergraduate (BS) degree in Statistics, Mathematics, Econometrics, Operations Research, Public Health, and Epidemiology or another related field. MS degree is preferred. 
  • Three plus (3+) years of professional work experience. 
  • Two plus (2+) years of experience involving quantitative data analyses for problem solving in US Healthcare industry. 
  • Two plus (2+) years of experience with predictive, forecasting, and optimization problem solving using data analytics tools like Python, R or SAS. 
  • Exposure of working with cloud Big Data Stack to orchestrate data gathering, cleansing, preparation and modelling preferred. 
  • Advanced SQL skills working with RDBMSs such as Oracle, SQL Server, etc. 
  • Experience working with data visualization tools or Data Visualization Designers in Tableau or Power BI. 
  • Also, experience with data visualization for analytic models in Rshiny, GGPlot, Qlik, Alteryx, Flask, D3, etc. used to tell the data story to business users to foster adoption of analytic outputs created preferred. 
  • Exceptionally skilled in machine learning, data analytics, pattern recognition and predictive modelling.
  •  Strong communication and presentation skills. Effective communication and storytelling skills. 
  • Energy and enthusiasm. Passion for learning and contributing to development. A true team player. Collaborative mindset for effective communication across teams.

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