Data Engineer, Pharmacy Data, SQL Server
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Job Description
Remote Data Engineer building SQL Server pharmacy data pipelines for Chiri’s AI operating platform. Ensuring reliable ingestion, quality, observability, and high availability.
Responsibilities:
- Work with Medi-Span, NCPDP, NDCs, NPIs, and related pharmacy claims and reference datasets
- Design and build secure ingestion pipelines using SFTP, structured flat-file drops, and third-party data feeds
- Optimize SQL Server performance, analyze execution plans, improve query efficiency, and manage indexed/materialized view strategies
- Work with SQL Server Always On Availability Groups and reliable database operations
- Implement validation rules, constraints, reconciliation, deduplication, schema monitoring, and exception handling for incoming third-party data
- Build monitoring to track ingestion, data freshness, failures, integrity, completeness, and processing performance
Requirements:
- Hands-on experience with pharmacy claims, reference data, and industry identifiers, including Medi-Span, NCPDP, NDC, and NPI
- Strong SQL Server and T-SQL development experience
- Experience with SQL Server Always On Availability Groups
- Advanced SQL performance tuning, execution-plan analysis, indexing, and query optimization
- Experience building reliable SFTP-based and flat-file ETL/ELT pipelines
- Experience designing data quality frameworks, validation constraints, and monitoring for third-party feeds
- Experience building operational dashboards, alerts, and observability for data pipelines
- Strong understanding of data lineage, reconciliation, security, and production support
- Preferred: Experience with pharmacy rebate processing, PBMs, TPAs, or manufacturer reporting
- Preferred: Experience with Python-based data engineering and automation
- Preferred: Experience handling PHI and HIPAA-regulated data
- Preferred: Experience integrating high-volume batch pipelines with near-real-time applications
- Preferred: Experience with on-call rotations and availability
Benefits:
- The opportunity to build the data foundation of a new platform where accuracy, reliability, and performance directly affect business outcomes.
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