Lead Analytics Engineer
Core
Design and develop data integrations to deliver Enterprise BI Data Marts and BI Semantic Data Layers, leveraging AI-assisted capabilities for pipeline optimization.
Role type
Lead Analytics Engineer
Builds
Enterprise BI Data Marts, BI Semantic Data Layer(s), end-to-end data integration and analytics engineering pipelines
Domain
Healthcare, Data Engineering, Business Intelligence
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Data integration, Business Intelligence Architecture, Universal semantic model design, Hadoop tech stack (HDFS, Hive, HQL, Spark, Scala, Pyspark), SQL, MPP platforms (Teradata), Azure Cloud Analytics (Synapse, ADLS, ADF, Azure SQL), DevOps/CI/CD, Enterprise scheduling tools
Preferred skills
Databricks (Spark transformations, scalable pipelines), Power BI (Semantic Model design, performance optimization), Databricks GenAI features, Healthcare domain data experience
Technologies
Teradata, Hadoop, Azure Databricks, GitHub Copilot, Databricks GenAI, Power BI Copilot, Control M, Zena, Synapse, ADLS, ADF, Azure SQL, Hive, Spark, Scala, Pyspark
Responsibilities
Design and develop data integrations for BI Data Marts and Semantic Layers; lead multiple projects and provide technical guidance; support team members in the DAS organization; develop modern data engineering pipelines using AI-assisted capabilities; work with business stakeholders to design data product solutions
Seniority
Senior, hands-on IC with leadership responsibilities