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BI Engineer
Spire Orthopedic PartnersData Engineer building and maintaining scalable data pipelines for healthcare analytics. Collaborating with various teams to ensure data reliability and support production workflows.
Posted 7/10/2026full-timeRemote • Connecticut • 🇺🇸 United StatesMid-LevelSenior💰 $113,200 - $169,800 per yearWebsite
Tech Stack
Tools & technologiesAirflowAzureCloudETLMatillionPythonSQL
About the role
Key responsibilities & impact- Design, build, and maintain scalable data pipelines that ingest, transform, and publish data from practice management, EHR, billing, finance, and operational source systems.
- Develop and optimize SQL-based data models in Snowflake to support Power BI reporting, executive dashboards, recurring analytics, and ad hoc business analysis.
- Use dbt or similar transformation frameworks to create tested, version-controlled, and documented data models.
- Build data integration processes using APIs, SFTP files, flat files, database extracts, and third-party vendor feeds.
- Create automated data quality checks, reconciliation processes, anomaly detection routines, and alerting to identify issues before they affect downstream reporting.
- Partner with analytics, finance, RCM, and operations stakeholders to translate reporting needs into reliable data structures and reusable datasets.
- Improve data reliability by standardizing definitions, mapping source system fields, documenting lineage, and resolving data inconsistencies across systems.
- Tune query performance, manage large datasets efficiently, and troubleshoot pipeline failures or report performance issues.
- Support secure data handling practices, access controls, and HIPAA-aligned data governance expectations for healthcare information.
- Maintain clear technical documentation, including source-to-target mappings, transformation logic, data dictionaries, and operational runbooks.
- Collaborate using Git-based workflows, code review, and deployment practices appropriate for production data environments.
- Provide production support for scheduled data jobs, recurring reporting datasets, and critical analytics workflows.
Requirements
What you’ll need- 4+ years of experience in data engineering, analytics engineering, business intelligence engineering, or a closely related technical data role.
- Strong SQL skills, including complex joins, window functions, CTEs, query optimization, data validation, and performance tuning.
- Hands-on experience with Snowflake or another modern cloud data warehouse.
- Experience building ELT/ETL pipelines and transforming raw source data into modeled, analysis-ready datasets.
- Proficiency with Python for automation, data processing, validation, or pipeline support.
- Experience with dbt, Airflow, Dagster, Fivetran, Matillion, Azure Data Factory, or comparable data transformation/orchestration tools.
- Understanding of dimensional modeling, semantic layers, data marts, and structures that support reliable BI reporting.
- Working knowledge of Power BI datasets, Power Query, DAX, or BI consumption patterns, even if dashboard development is not the primary focus.
- Comfortable working with messy, high-volume, multi-source data and turning it into clean, trustworthy, documented outputs.
- Strong problem-solving skills and the ability to troubleshoot data issues from source extraction through final report output.
- Clear communication skills, including the ability to explain technical issues and tradeoffs to non-technical stakeholders.
- High attention to detail, strong ownership, and a low tolerance for unexplained data discrepancies.
Benefits
Comp & perks- Excellent growth and advancement opportunities
- Dynamic environment
- Access to a diverse network of practitioners
- Broad infrastructure of tools and programs to enhance the employee experience
- Competitive Compensation
- Generous PTO
- Benefits package: health, dental, vision, 401(k), etc.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLData ModelingData Pipeline DevelopmentData ValidationPerformance TuningDimensional ModelingData Quality ChecksAnomaly DetectionData GovernanceData Documentation
Soft Skills
Problem-SolvingClear CommunicationAttention to DetailOwnership