Data Warehouse Architect

Data Engineering Lead excels in data modeling, Lakehouse, and ML products delivery using an agile DevOps framework with a mastery of distributed data architectures essential for data, analytical and operational ML applications with demonstrated proficiency in frameworks including DataBricks, Sagemaker, Spark, Kafka, Kubernetes, SQL, NoSQL DBs, Graph DBs, and visualization tools such as Power BI/Tableau.

The Data Engineer Lead serves as the primary State of Michigan technology lead engaging with the UoM proof of concept team to support best practice adoption within the state hosting environment and provides training to DAV data engineers.

Job Duties

• Oversee the design, development, and maintenance of data pipelines that move, transform, and prepare data for analytics and operational systems.
• architect and optimize data infrastructure, including storage solutions, orchestration frameworks, and ETL/ELT processes.
• Ensure data quality, reliability, and security by establishing standards, monitoring systems, and implementing validation and governance practices.
• Lead and mentor data engineering staff, providing technical guidance, reviewing designs/code, and supporting professional growth.
• Collaborate with cross functional partners, such as data scientists, analysts, product teams, and business stakeholders, to ensure data solutions meet organizational needs and strategic goals

Requirements

4 years:

• Hands-on experience is require in hydrting the enterprise Data Lake on a Cloud Service Provider (AWS, Azure, or Google) from relational, semi- structured and unstructured data sources by building Extract and Load Data Pipelines.
• Hands-on experience is required in Transforming the datasets in a Data Lake on a Cloud Service Provider to deliver Data Products with traceability of their attributes / features to the Critical Data Elements in the systems of record.

2 years:

• Experience is required in enforcing Data Sharing Policies to Data Products to ensure that User get to see only the version of the Data Product the User is entitled to get access to at the time of subscription.

Desired Skills

• Proficiency desirable in DevOps tools including Github/Jenkins/Terraform/YAML/DAGs/Docker/Databricks/SageMaker etc. for building
• Data/ML pipelines to extract/store data from multiple sources to parquet destinations.
• Experience desirable in promoting Data Engineering Standards and Best Practices among the community of developers to influence the enterprise towards building scalable and supportable Data/ML Products delivery and their usage by the community of data, analytics, and ML product users.
• Experience desirable in implementing Data Governance and Data Security tools available on a CSP to automate the enforcement of Data Sharing Policies at the point of subscription of a Data Product by a subscriber.

Other Desired Skills:

4 years:

• Exerience in modeling and leveraging Relational data services with demonstrated proficiency in Python/Pysparks/SQL programming and tuning SQL queries to extract data from multiple sources ( relational DB, flat files, CSV, HTML, JSON, etc) sources into Lakehouse Medallion architecture in parquet formats
• Experience in designing and implementing data, analytics, and AI solutions for large enterprises by building data pipelines using the available data platform tools of any Cloud Service Provider (CSP) such as AWS/Microsoft/Google.
• Programming/scripting languages including Python, R, Spark, etc.

Must have a BS in Computer Science / Data Science / Information Systems

Experience in designing and delivering Star-schema based operational data store is required to enable visualization of program activities and outcomes in a visualization tool such as Power BI.

Key Programming Languages: SQL, Python, R, Spark, Terraform Scripting, DAGs Scripting, YAML scripting, Docker Other Technologies, Concepts and Frameworks: Juniper Notebooks, NOSQL DB, Graph DB, Parquet DB, Lakehouse and Medallion Architecture concepts, Kafka, Kubernetes, Glue, Databricks, Power BI, Tableau, Redshift Spectrum, Sagemaker, DBT, Datahub, SageMaker, Machine Learning, GitHub, DevOps

Minimum Education

• Bachelor's Degree

Location

• Local candidates vs non-local: Open to candidates local to the Lansing Michigan area and those willing to relocate. Candidates that relocate must relocate before day one and be ready to be on-site from day one at their own expense (non-negotiable)
• Position is a hybrid schedule with Wednesday and Thursday are REQUIRED in-office days. This is NON-NEGOTIABLE and there is NO remote only option.
• Working hours Monday-Friday, approximately 8:00 a.m. to 5:00 p.m.

Additional

Requirements

• Must be authorized to work in the United States; We are unable to offer sponsorships at this time
• Must undergo a background check and drug screening for employment.

Employment Terms

• This is a W2 position
• 40 hrs per week
• HYBRID schedule - Wednesday and Thursday are REQUIRED in-office days. This is NON-NEGOTIABLE and there is NO remote only option.

About Zenfreed

At Zenfreed, we are more than an IT company. We bridge the gap between people wanting to do the work they were meant to do and organizations needing the right talent.

We are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

Benefits

We understand a comprehensive benefits package is crucial to employment satisfaction. We offer medical, dental and vision coverage options for all employees.