Senior Data Scientist — Data Engineering & Analytics Leader

Seneca Holdings

United States

On-site

USD 120,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Life and disability insurance

Job summary

Three Sisters Federal is seeking a Senior Data Scientist to support a DoD Veterans Affairs (VA) health system, focusing on workforce analytics and reporting. You will blend data engineering (SQL Server ETL) with analytics delivery (Power BI models, dashboards) and drive modernization efforts across data pipelines and governance.

The role combines hands-on development with design oversight, including tool selection, deployment pipelines, and reproducible analytics workflows.

Qualifications

5+ years in data science, data engineering, or advanced analytics.
Advanced SQL with on-premises SQL Server, performance tuning.
Strong Python for data work with SQL Server access.
Power BI development experience including semantic models.
Experience building ETL processes (SSIS or comparable).
Analytical methods: regression, classification, time series, clustering.
Version control and Python environment management.
Ability to design options with trade-offs for tooling and infrastructure.
Clear documentation and communication to non-technical stakeholders.
U.S. citizen; VA background check/PIV credential required.

Responsibilities

Build and maintain a SQL Server data warehouse with ETL from multiple apps and SharePoint.
Replace cursor-based data cleansing with Python-based processing.
Document ETL workflows and interdependencies to reduce technical debt.
Design pipeline orchestration outside SQL Server; evaluate tools, present recommendations, implement approved approach.
Establish source control and dependency management for reproducible analytics code.
Design repeatable deployment process for ETL and analytics code from development to production.
Design, build, and maintain Power BI semantic models, reports, and dashboards.
Diagnose and resolve Power BI performance problems and optimize models.
Develop Python visuals in Power BI and publish interactive outputs outside the canvas.
Respond to rapid-turnaround data requests from leadership and external inquiries.
Define KPIs and build reporting standards and templates.