Hiring: Data Warehouse Architect 3 / Data Engineering Lead
Location: Lansing, MI
Work Mode: Hybrid – Onsite Wednesday & Thursday (Mandatory)
Duration: 6+ Months (Possible Extension)
Employment Type: C2C
Visa: No OPT/CPT
Education: Bachelor's Degree Required
Location Requirements
Candidates local to the Lansing, MI area are preferred.
Relocation candidates are welcome.
Candidates willing to relocate must complete relocation before Day 1.
Candidates must be available to work onsite from Day 1.
Relocation expenses must be covered by the candidate.
Wednesday and Thursday are mandatory onsite days.
Job Summary
We are looking for an experienced Data Warehouse Architect / Data Engineering Lead with strong expertise in Cloud Data Engineering, Data Lakehouse, Medallion Architecture, Data Modeling, and Enterprise Data Pipelines.
The ideal candidate should have hands-on experience building scalable ETL/ELT pipelines, transforming structured and unstructured data, implementing data governance and security policies, and delivering enterprise-level Data and ML products using AWS, Azure, or Google Cloud Platform.
Mandatory Technical Skills
4+ years of hands-on experience in Cloud Data Engineering (AWS/Azure/Google Cloud Platform).
4+ years of experience building ETL/ELT pipelines and ingesting data from relational, semi-structured, and unstructured sources.
4+ years of experience in Data Lakehouse and Medallion Architecture (Bronze, Silver, Gold).
4+ years of experience in Data Transformation, Data Modeling, and Data Product development.
4+ years of Python, PySpark, Spark, and SQL programming.
2+ years of experience implementing Data Sharing Policies, Data Governance, and access controls.
Strong experience with Star Schema, Data Warehousing, and Operational Data Stores.
Experience with Parquet file formats and large-scale distributed data processing.
Experience designing and delivering Power BI/Tableau dashboards.
Preferred Technical Skills
AWS Glue, Redshift, Redshift Spectrum, and SageMaker.
Azure Data Services / Google Cloud Data Services.
Databricks, DBT, Apache Spark, and Kafka.
Kubernetes, Docker, and Jupyter Notebooks.
Terraform, GitHub, Jenkins, YAML, and CI/CD.
DAGs and workflow orchestration.
NoSQL and Graph Databases.
DataHub and Data Governance/Security tools.
Machine Learning and Data/ML Pipeline development.
Power BI and Tableau.
Key Responsibilities
Lead the architecture, development, and maintenance of enterprise data pipelines.
Design and optimize Cloud Data Lake and Lakehouse architectures.
Implement Medallion Architecture for scalable data processing.
Build and manage ETL/ELT pipelines from multiple enterprise data sources.
Ensure data quality, lineage, traceability, security, and governance.
Implement data-sharing policies and role-based access controls.
Design Star Schema-based Operational Data Stores.
Collaborate with data scientists, analysts, and business stakeholders.
Mentor and provide technical guidance to data engineering teams.
Establish enterprise data engineering standards and best practices.
Support the State of Michigan's data engineering initiatives and provide technical guidance and training to data engineers.
Required Education
Bachelor's Degree in Computer Science, Data Science, Information Systems, or a related field.
Ideal Candidate Profile
We are looking for candidates with strong experience in:
Cloud Data Engineering + Data Warehouse Architecture + Lakehouse Architecture + Python/PySpark + SQL + Data Governance + AWS/Azure/Google Cloud Platform.
