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Senior Big Data Engineer Jobs in Michigan (NOW HIRING)

Mindlance

Big Data Developer

Detroit, MI · On-site

$52.25 - $68/hr

They are seeking a Big Data Developer to install, configure, and administer Cloudera clusters, as well as develop functionality within Hadoop clusters and manage data files in HDFS. Responsibilities ...

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 ... Experience with big data technologies such as Apache Spark, Hadoop, Kafka, and Flink. * Experience ...

FastTek

Data Engineer

Dearborn, MI

$105K - $126K/yr

GCP, Big Data, Data Warehousing, Artificial Intelligence & Expert Systems, API * GCP - Experience ... Senior Data Engineer with 7+ years in data engineering and 10+ years in software with AI ML ...

FastTek

Data Engineer

Dearborn, MI

$105K - $126K/yr

GCP, Big Data, Data Warehousing, Artificial Intelligence & Expert Systems, API * GCP - Experience ... As a Senior Data Engineer, you will architect and scale end-to-end data pipelines on GCP ...

Saransh Inc

GCP Data Engineer with Python

Dearborn, MI · On-site

$105K - $126K/yr

Exposure to Big Data ecosystems and distributed data processing. Nice to have Technical Skills: * Prior experience with ETL tools like DataStage or Informatica. Responsibilities: * The Data Engineer ...

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 ... Big Query, Azure, AWS S3, etc.) • Familiarity with time series database, data streaming ...

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 ... Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS ...

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 ... Comprehensive experience working with Big Data platforms (i.e., Spark, Google Big Query, Azure, AWS ...

Stefanini Group

GCP Data Engineer

Dearborn, MI · On-site

$61 - $66/hr

NoSQL, Kubernetes, Kafka, GCP, Cloud Architecture, Data Architecture, Big Data, Cloud ... Expert proficiency in programming languages such as Python or Scala. * Advanced SQL skills for ...

Stefanini Group

GCP Data Engineer

Dearborn, MI

$105K - $126K/yr

NoSQL, Kubernetes, Kafka, GCP, Cloud Architecture, Data Architecture, Big Data, Cloud ... Expert proficiency in programming languages such as Python or Scala. * Advanced SQL skills for ...

Stefanini Group

GCP Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

NoSQL, Kubernetes, Kafka, GCP, Cloud Architecture, Data Architecture, Big Data, Cloud ... Expert proficiency in programming languages such as Python or Scala. * Advanced SQL skills for ...

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Senior Big Data Engineer information

See Michigan salary details

$13

$54

$76

How much do senior big data engineer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for senior big data engineer in Michigan is $54.89, according to ZipRecruiter salary data. Most workers in this role earn between $46.73 and $61.83 per hour, depending on experience, location, and employer.

What is the difference between Senior Big Data Engineer vs Data Architect?

AspectSenior Big Data EngineerData Architect
CredentialsBachelor's/Master's in CS, Data Science, or related; experience with Hadoop, SparkBachelor's/Master's in CS, Data Science, or related; certifications like TOGAF, cloud architecture
Work EnvironmentDevelops, implements, and maintains data pipelines and systemsDesigns overall data infrastructure and architecture strategy
Employer & Industry UsageTech companies, finance, healthcare, retailLarge enterprises, consulting firms, cloud providers
Search & Comparison IntentUnderstanding technical roles, skills, and responsibilitiesFocus on data system design and strategic planning

While both roles work with data systems, a Senior Big Data Engineer primarily develops and maintains data pipelines and systems, whereas a Data Architect designs the overarching data infrastructure and strategy. The roles often collaborate but differ in scope and focus within data management.

How does a senior big data engineer collaborate with data scientists and business stakeholders?

As a Senior Big Data Engineer, you'll frequently work alongside data scientists to design and maintain data pipelines that ensure reliable and accessible data for modeling and analytics. Collaboration with business stakeholders is also essential, as you'll help translate business requirements into technical data solutions, ensuring that data architecture supports organizational goals. Regular meetings, code reviews, and cross-team project planning are common, making strong communication and a collaborative mindset vital for success in this role.

What skills and qualifications are needed to be a senior big data engineer?

To thrive as a Senior Big Data Engineer, you need advanced expertise in data architecture, distributed computing, and programming languages such as Java, Scala, or Python, typically backed by a degree in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, Kafka, and cloud platforms, as well as relevant certifications (e.g., Cloudera, AWS), is highly valuable. Strong problem-solving, communication, and leadership skills set outstanding candidates apart, especially when collaborating with cross-functional teams. These competencies are critical for designing scalable data solutions, ensuring data quality, and driving impactful business insights.

What is a senior big data engineer?

Senior Big Data Engineers are advanced-level professionals who design, build, and maintain large-scale data processing systems. They work with technologies such as Hadoop, Spark, and NoSQL databases to handle massive amounts of data efficiently. Their responsibilities often include optimizing data pipelines, ensuring data quality, and collaborating with data scientists and analysts to support business needs. Senior Big Data Engineers also mentor junior team members and help drive architectural decisions related to data infrastructure.
What are popular job titles related to Senior Big Data Engineer jobs in Michigan? For Senior Big Data Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Senior Big Data Engineer jobs in Michigan look for? The top searched job categories for Senior Big Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Senior Big Data Engineer jobs? Cities in Michigan with the most Senior Big Data Engineer job openings:
Senior Big Data Engineer jobs near you
Infographic showing various Senior Big Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $114,179 per year, or $54.9 per hour.

Senior Big Data Engineer

Pi Square Technologies LLC

Farmington Hills, MI • On-site

$54.75 - $72.50/hr

Full-time

Posted 5 days ago

Job description

Senior Big Data Engineer
Data Engineer
Owns the data pipelines that move data from operational source systems onto the data platform extraction, ingestion, transformation, orchestration, and the day-to-day operational health of those pipelines.
Also plays a role as a hands-on builder of Foundational Data Products (raw record-of-truth) and potentially Derivative Data Products (composed from upstream products).
Core skills
SQL & Python (table stakes); Scala/Java for high-throughput streaming
Pipeline build & operations: design, develop, deploy, monitor, and remediate batch and streaming pipelines that land source data on the platform; manage backfills, replays, late-arriving data, schema drift, and SLA breaches
Ingestion patterns: full-load, incremental, change-data-capture (Debezium, Fivetran, Qlik Replicate, GoldenGate), event-driven ingest, API and file-based
intake
Pipeline frameworks: dbt, Apache Spark, Apache Beam, Airflow, Dagster, Prefect
Streaming: Kafka, Kinesis, Flink, Spark Structured Streaming
Data product packaging: schema contracts (Avro/Protobuf/JSON Schema), versioning, SLAS/SLOs, data contracts, output-port design (SQL, file, API, event)
Storage formats: loeberg, Delta Lake, Hudi (open table formats are now the mesh default)
Quality & observability: Great Expectations, Soda, Monte Carlo, dbt tests, data lineage (OpenLineage)
CI/CD for data: GitOps pipelines, unit + integration tests, environment promotion
Al-adjacent vector store ingestion (pgvector, Pinecone), feature stores (Feast, Tecton), RAG-ready chunking and embedding pipelines
Mesh-specific: knowing when to build a derivative product vs. extending an existing one; consuming upstream products through governed input ports rather than reaching into source systems

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