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Data Engineering Jobs in Howell, MI (NOW HIRING)

Freudenberg Group

Data Engineer

Plymouth, MI · On-site

$120K/yr

Degree in Computer Science, Data Engineering, or related field (or equivalent experience). * Proven experience building and running production data pipelines and data products. * Strong Python ...

Freudenberg

Data Engineer

Plymouth, MI

$120K/yr

Degree in Computer Science, Data Engineering, or related field (or equivalent experience). * Proven experience building and running production data pipelines and data products. * Strong Python ...

Birdi

Principal Data Engineer

Plymouth, MI · Remote

$109K - $130K/yr

Principal Data Engineer Company: Birdi Work Type: Remote Employment: Full Time Location: US Seniority: Senior Level Technologies: Tableau, Tableau Server, SSIS, SQL Server, PostgreSQL, Python, SSRS ...

Venteon

Senior Director Data Analytics & AI

Novi, MI · On-site

Partner closely with executive leadership, business stakeholders, engineering, and IT teams to identify and deliver data-driven business outcomes. * Build, mentor, and lead high-performing global ...

NITS Solutions

Data and Security Manager

Novi, MI · On-site

The position acts as a critical bridge between data engineering, analytics teams, and client security requirements. Key Responsibilities • Establish and enforce data governance frameworks for ...

Stem Xpert

Data Engineer

Plymouth, MI

$109K - $130K/yr

Work as SQL Server d/base admin & set up SQL security Audit & write prgms for Big Data solutions. * Conduct user acceptance testing & integration testing. Master's deg in Comp Sci, Engg or related ...

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All JobsData Engineering JobsData Engineering Jobs in Howell, MI

Data Engineering information

See Howell, MI salary details

$43K

$154.4K

$227.9K

How much do data engineering jobs pay per year?

As of Jul 7, 2026, the average yearly pay for data engineering in Howell, MI is $154,420.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,900.00 and $159,100.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

What are the key skills and qualifications needed to thrive in the Data Engineering position, and why are they important?

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

What cities near Howell, MI are hiring for Data Engineering jobs? Cities near Howell, MI with the most Data Engineering job openings:
Data Engineering jobs near you
Data Engineer (Brighton MI Office)

Data Engineer (Brighton MI Office)

Common Sail Investment Group

Brighton, MI • On-site

$109K - $131K/yr

Other

Posted 20 days ago

Job description

Data Engineer

CommonSail Investment Group

Location: Brighton, Michigan

Overview: As a Data Engineer, you will design, build, and maintain the data infrastructure within CommonSail Investment Group. You will work at the intersection of senior housing data, healthcare operations data and modern data engineering building robust pipelines, maintaining our Snowflake cloud data lake, developing APIs, and partnering with IT and data professionals to ensure the right data reaches the right people at the right time. This role is pivotal in ensuring that CommonSails data assets are accurate, secure, accessible, and leveraged effectively to support strategic business initiatives and operational excellence.

Qualifications:

  • Bachelors degree in Information Systems, Computer Science, Data Science, or a related field.
  • 3 - 7 years of experience in data engineering, data infrastructure, API development, data integration, and data governance.
  • Strong command of SQL and Python for data transformation, automation, and pipeline development
  • Demonstrated hands-on experience with Snowflake, including performance tuning, clustering, and access control.
  • Proficiency with dbt (data build tool) for transformation layer development, testing, and documentation.
  • Experience building and consuming RESTful APIs, with working knowledge of authentication patterns (OAuth 2.0, API keys).
  • Knowledge of data privacy, compliance, and security standards (e.g., HIPAA, GDPR).
  • Strong communication, problem-solving, and analytical skills.
  • Experience in healthcare, long-term care, or related regulated industries familiarity with PointClickCare, MatrixCare, or similar EHR/EHR-adjacent systems is a strong plus.

Primary Responsibilities:

  • Data Pipelines: Design, build, and maintain scalable data pipelines for ingestion, transformation, and delivery of healthcare operations data from multiple client systems and third-party sources.
  • Data Architecture & Administration: Architect and administer the organization's Snowflake data warehouse, including database design, role-based access control, query optimization, and cost governance.
  • DBT: Develop and maintain dbt models for data transformation, testing, documentation, and lineage across all data domains (census, financials, clinical, acquisition targets).
  • API Development: Build and maintain RESTful APIs and integration services that connect source systems, internal tools, and analytical platforms.
  • Data Lake Administration: Design and implement data lake strategies for raw data storage, archival, and cost-efficient processing of high-volume datasets.
  • Data Modeling: Create and enforce data modeling standards dimensional modeling, star/snowflake schemas, and normalized models across the enterprise data warehouse.
  • Stakeholder Collaboration: Partner with business leaders and technical teams to align data strategy with organizational goals, translating requirements into scalable solutions.
  • Performance Monitoring: Monitor pipeline health, establish alerting and data quality checks, and resolve incidents with urgency and rigor.
  • Data Support: Support business operation engagements with data room analysis, source system evaluation, and integration planning for EHR entities.
  • Data Engineering Practices: Champion data governance, documentation, and best practices across the data engineering function.

Skills:

  • Cloud Data Warehousing (Snowflake): Design, administer, and optimize cloud-based data warehouses, including schema design, performance tuning, cost governance, security, and role-based access control.
  • Data Transformation & Modeling: Develop scalable transformation layers using dbt and SQL, implementing dimensional and normalized models to support analytics and downstream consumption.
  • Programming & Analytics: Use Python and SQL for data transformation, automation, pipeline logic, and analytical problem-solving across batch and event-driven workloads.
  • Data Pipelines & Orchestration (ETL / ELT, Airflow or Similar): Build, schedule, and monitor ETL/ELT pipelines with orchestration tools to ensure timely, accurate, and resilient data processing.
  • Data Ingestion & Integration (Fivetran, Airbyte, APIs): Ingest data from SaaS platforms, databases, and systems using managed connectors and custom integrations, ensuring scalability and data reliability.
  • API Development & Data Services (REST APIs, JSON): Design and consume RESTful APIs to exchange data between systems, using standard formats such as JSON and secure authentication patterns.
  • Cloud Platforms & Supporting Technologies (AWS, Azure, GCP): Leverage major cloud platforms and supporting services for storage, compute, networking, and security to build flexible and scalable data solutions.
  • Data Storage Formats & Lakes (Data Lakes, Parquet, Avro): Implement data lake architectures using efficient, columnar storage formats to support large-scale analytics, archival, and cost-effective querying.
  • Development Practices & Tooling (Git, VS Code, Database Administration): Apply modern development workflows using version control, IDEs, and database administration best practices to maintain high-quality, well-documented data systems.

General Working Conditions: While performing the duties of this job, the employee is required to communicate effectively with others, sit, stand, walk, and use their hands to handle the keyboard, telephone, paper, files, and other equipment and objects. The employee is occasionally required to reach with hands and arms. This position requires the ability to review detailed documents and read computer screens. The employee will occasionally lift and/or move up to 25 pounds. The work environment requires appropriate interaction with others. The noise level in the work environment is moderate. Occasional travel to different locations may be required.

Equal Opportunity Employer

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