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Senior Data Analytics Engineer Jobs in Michigan (NOW HIRING)

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$140K - $200K/yr

As a Senior Data Engineer at Mariana, you'll own a data domain end-to-end-designing the pipelines ... Model time-series and analytical plant data for both human analysis and machine learning training ...

Mariana Minerals

Sr. Data Engineer

Ann Arbor, MI · On-site

$103K - $140K/yr

They are seeking a Senior Data Engineer to design and build data pipelines that ensure the ... analytical results--including schema design, orchestration, reliability, and the contract it ...

Stellantis

Senior Data Engineer

Auburn Hills, MI · On-site

$100K - $136K/yr

About the Role Join the Supply Chain AI Hub as a Senior Data Engineer helping turn AI ambition into ... Ability to collaborate effectively with analytics, AI, and software engineering teams Our Benefits ...

Stantec

Senior Data Architect

Detroit, MI · On-site

$66.50 - $89/hr

Senior Data Architect We are seeking a Senior Data Architect to join a project team that will be ... developers, Business Analysts, and Project Management - to plan and execute PM2PA data-related ...

Corning

$104K - $125K/yr

... analytics, artificial intelligence, and data-driven decision-making? Join Corning's Optical ... As a Senior Data Engineer, you will design, build, optimize, and maintain scalable data pipelines ...

HTC Global Services

Senior Data Engineer

Dearborn, MI · On-site

$97K - $132K/yr

Job Title: Senior Data Engineer Overview We are seeking an experienced Senior Data Engineer to ... Strong analytical, problem-solving, and critical thinking skills. * Excellent communication and ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Stellantis is looking for a Senior Data Engineer to join their AI & Data Analytics Team. In this role, you will be responsible for designing, building, and optimizing robust data pipelines that ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

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 ...

Orbion Space Technology

Senior Data Engineer

Houghton, MI · On-site

$90K - $122K/yr

Job Type Full-time Description SENIOR DATA ENGINEER Orbion is seeking a Senior Data Engineer/Software Developer Orbion help build and maintain Orbion's internal application platform and enterprise ...

Kiongroup

Senior Data Engineer

Grand Rapids, MI · On-site

$133K - $204K/yr

We are seeking a dynamic and highly skilled Senior Data Engineer who has extensive experience ... Collaborate with data scientists, analysts, and cross functional teams to design data models ...

Cognizant Technologies

MI

$102K - $139K/yr

Duration : 1 year Qualifications The Senior Data Engineer will implement data-oriented solutions to ... Leads analysis, model and design the application data structure, storage, integration, deployment ...

QUANTUM TECHNOLOGIES LLC

Data Analyst

Brooklyn, MI · On-site

$80/hr

Brooklyn, NY 11201 The Senior Data Analyst with ETL Expertise shall provide Client Data Management team with technical expertise for the completion of Data Profiling/Cleansing, Conversion/Migration ...

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All JobsData Analytics Engineer JobsSenior Data Analytics Engineer JobsSenior Data Analytics Engineer Jobs in Michigan

Senior Data Analytics Engineer information

See Michigan salary details

$70.6K

$110.1K

$152.5K

How much do senior data analytics engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for senior data analytics engineer in Michigan is $110,107.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $125,500.00 per year, depending on experience, location, and employer.

What is the difference between Senior Data Analytics Engineer vs Data Scientist?

AspectSenior Data Analytics EngineerData Scientist
CredentialsBachelor's/Master's in Data Science, Computer Science, or related fieldsBachelor's/Master's in Data Science, Statistics, or related fields
Work EnvironmentFocus on data pipelines, analytics tools, and reporting systemsFocus on model development, statistical analysis, and predictive modeling
Industry UsageUsed in analytics teams to build data infrastructure and insightsUsed in R&D, product development, and research teams for modeling

While both roles require strong analytical skills and similar educational backgrounds, Senior Data Analytics Engineers primarily focus on building and maintaining data infrastructure and delivering insights through analytics tools. Data Scientists, on the other hand, concentrate on developing predictive models and statistical analysis. The roles often collaborate but serve different functions within data-driven organizations.

How does a senior data analytics engineer typically collaborate with cross-functional teams to deliver insights?

As a Senior Data Analytics Engineer, you will frequently work with stakeholders in product, marketing, and engineering to translate business needs into data solutions. This involves gathering requirements, designing and building data pipelines, and presenting actionable insights. Effective communication and regular meetings with team members ensure that data models and dashboards align with business objectives. You may also mentor junior analysts and engineers, fostering a collaborative and knowledge-sharing environment.

What does a senior data analytics engineer do?

A Senior Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines and analytical solutions. They work closely with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability. Their role often includes optimizing data workflows, implementing best practices in data management, and mentoring junior team members. Additionally, they help translate business needs into technical solutions to support data-driven decision making.

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

To thrive as a Senior Data Analytics Engineer, you need expertise in statistics, data modeling, and programming languages such as Python or SQL, typically backed by a degree in computer science, engineering, or a related field. Experience with data analytics tools (e.g., Tableau, Power BI), cloud platforms (e.g., AWS, Azure), and relevant certifications like Google Data Engineer are highly valued. Strong problem-solving, communication, and leadership skills help you translate complex data insights into actionable business strategies and mentor junior team members. These capabilities are crucial for delivering accurate data-driven solutions that drive organizational decision-making and innovation.
What are the most commonly searched types of Data Analytics Engineer jobs in Michigan? The most popular types of Data Analytics Engineer jobs in Michigan are:
What are popular job titles related to Senior Data Analytics Engineer jobs in Michigan? For Senior Data Analytics Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Senior Data Analytics Engineer jobs in Michigan look for? The top searched job categories for Senior Data Analytics Engineer jobs in Michigan are:
What cities in Michigan are hiring for Senior Data Analytics Engineer jobs? Cities in Michigan with the most Senior Data Analytics Engineer job openings:
Senior Data Analytics Engineer jobs near you
Infographic showing various Senior Data Analytics Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, 1% Temporary, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $110,107 per year, or $52.9 per hour.

Sr. Data Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$140K - $200K/yr

Full-time

Re-posted yesterday

Job description

About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
The Role
Mariana Minerals is building the critical minerals supply chain from the ground up-and we're looking for a Senior Data Engineer to help make it autonomous.
We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities. Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027.
As a Senior Data Engineer at Mariana, you'll own a data domain end-to-end-designing the pipelines, schemas, and contracts that make a whole class of plant data trustworthy and queryable. The systems you build are the foundation every model and every operational decision depends on.
The Tech
This is some of the most interesting applied data work happening today.
Our internal platform, PlantOS, uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots-but applied to autonomous, short-interval control of mineral refining circuits. None of it works without data: every set point those models adjust, and every decision we make about a plant, rests on turning messy industrial reality into trustworthy, queryable, model-ready data.
The environment is noisy and non-stationary: sensors drift, lab results arrive late and malformed, wastewater compositions shift, equipment ages. The data backbone has to keep up. The end goal is fully autonomous refining operations-and the pipelines you build are the foundation everything else stands on.
What You'll Do
  • Work across domains-for example, all plant sensor and historian data, or all lab and analytical results-including schema design, orchestration, reliability, and the contract it exposes to everyone downstream.
  • Design and evolve our fleet of pipelines that pull from messy industrial sources-sensors, lab systems, historians, imagery, and more-into our databases and warehouse.
  • Model time-series and analytical plant data for both human analysis and machine learning training, validation, and monitoring; own data quality, observability, and lineage in your domain.
  • Build the data architecture that feeds production ML-the training and monitoring layer-in partnership with the ML engineers who own the model-specific semantics.
  • Mentor earlier-career engineers and define the data contracts other teams build against.
  • Work the boundary with machine learning deliberately: you own the platform and the interface it exposes; ML engineers own the features and models built on top of it. The training and monitoring layer is shared ground you design together.
Desired Qualifications
  • 4-8+ years in data engineering or a closely related role.
  • Strong Python and SQL, with deep experience designing database and warehouse schemas, including time-series and/or analytical data.
  • Proven experience building reliable, orchestrated data pipelines and operating them in the cloud with containers and CI/CD.
  • Experience with data quality, observability, and lineage, and comfort with messy real-world sources-drifting sensors, malformed exports, and the quirks of industrial systems.
  • A self-starter comfortable in high-ambiguity environments, working directly with process engineers, ML engineers, and operations teams.
  • Bonus: experience feeding data to ML systems-training datasets, feature pipelines, model monitoring-or working with industrial, sensor, or historian data.
Why This Role
We own the projects, generate the data, and close the loop. Every facility we build makes the software smarter-and the next facility faster and cheaper.
Mining is one of the last major industrial sectors that hasn't been rebuilt with modern software. The opportunity here isn't a feature gap-it's entire workflows and systems that don't exist yet.
Your work will directly shape how critical minerals are produced at scale in the coming decades.
Our culture is built on three principles:
Extreme Ownership - We take full responsibility for outcomes, relentlessly driving toward solutions.
Engineer Out Requirements, then Automate - We simplify, optimize, and then automate for scale.
Share Your Legos - We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.
Join us as we build the future of responsible mineral sourcing and supply.

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