📢 HIRING: Lead Data Engineer – (Lansing, MI | Long-Term)
We are looking for a highly experienced Lead Data Engineer to support a long-term.in Lansing, MI. This is a 1+ year contract with likely extension, and candidates must be willing to come onsite for interviews and work in a hybrid model.
Location:Â Lansing, MI
Duration:Â 12+ months (extendable)
Work Authorization:Â USC, GC, GC EAD, H4 EAD
Interview:Â In-person onsite required
Key Responsibilities
Lead design & development of scalable, high-performance data solutions using AWS (S3 and related services).
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Build and optimize ETL / data pipelines and data integration workflows.
Work extensively with Databricks, ElasticSearch, Kibana, and S3 for analytics and search.
Implement and manage ElasticSearch for fast data retrieval and analysis.
Develop clean, efficient code in Python/Scala and build complex database systems on Oracle and other RDBMS.
Design logical & physical data models, stored procedures, functions, and data warehouse structures.
Support EHR / HL7-driven solutions and ensure data integrity and quality in healthcare-related environments.
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Participate in full SDLC: requirements, technical specs, design, development, testing, and deployment.
Work in Agile environments, leverage Git for source control, and support CI/CD (Azure DevOps experience is a plus).
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Required Experience
12+ years developing complex database systems.
8+ years with Databricks.
8+ years with ElasticSearch & Kibana.
8+ years with Python/Scala.
8+ years with Oracle.
5+ years building ETL processes / data pipelines.
5+ years with AWS (cloud-based data engineering).
5+ years with data warehousing, data visualization, and data integrity practices.
Experience with CMM/CMMI Level 3, Agile, and test-driven development.
3+ years (or more) exposure to CI/CD pipelines in Azure DevOps (nice to have).
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If you meet these criteria and are open to onsite interviews in Lansing, MI, please DM me your resume or send it to [Upgrade to PRO to see contact] with your hourly rate and work authorization. Immediate consideration for strong profiles.
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