Data Engineer

At VPL we modernize clinical supply chains to support healthier patients. Our technology-driven solutions and consultative customer experience empower health systems and outpatient pharmacies to build smarter, more resilient supply chains. With over 700 hospitals and a 97 percent customer retention rate, we’re trusted to deliver transparency, cost savings, and peace of mind.

VPL is looking for a hands-on Data Engineer who can combine strong engineering fundamentals with analytical problem-solving. You will help keep our current Microsoft SQL Server and SSIS data environment reliable while developing the skills and platform knowledge needed to support VPL’s transition to PostgreSQL and Snowflake.

This role supports both our enterprise data warehouse and production-critical ETL processes. The right candidate can troubleshoot a failed pipeline, optimize SQL, reconcile operational or financial data, and work with business partners to turn complex questions into trusted data solutions. Extensive Snowflake experience is not required; we value strong SQL, data engineering, and analytical capabilities with the ability and desire to grow into Snowflake and modern ELT practices.

Operate, monitor, troubleshoot, and improve SSIS packages and scheduled ETL jobs that support VPL’s enterprise data warehouse and production systems.

Diagnose pipeline failures, performance bottlenecks, data discrepancies, dependency issues, and incomplete or delayed loads; restore processing safely and document recurring solutions.

Develop and optimize complex T-SQL queries, stored procedures, views, functions, database jobs, and data transformations in Microsoft SQL Server.

Design, build, test, and
maintain data pipelines that integrate operational, logistics, customer, carrier, supplier, billing, and financial data.

Develop and
maintain dimensional models, relational models, reporting datasets, and other analytical data structures that are accurate, understandable, and performant.

Work with analysts, product managers, engineers, finance, operations, and other business partners to define metrics, business rules, source-to-target mappings, and data-quality expectations.

Reconcile data across source systems, production applications, financial processes, and analytical platforms; investigate anomalies and explain findings clearly.

Implement controls and alerts that
identify missing, duplicate, late, incomplete, or inconsistent data before it affects customers, reporting, or billing.

Improve pipeline reliability through
appropriate logging, monitoring, restartability, error handling, testing, source control, documentation, and deployment practices.

Help evaluate which existing SSIS workloads should be migrated, redesigned, replaced, or retired as VPL moves toward PostgreSQL, Snowflake, and modern ELT patterns.

Contribute to data migration, validation, parallel testing, and cutover activities while protecting the accuracy and continuity of critical data processes.

Use SQL, Python, statistics, visualization, or other analytical techniques to profile data, test assumptions,
identify patterns, and support business decision-making.

Maintain data lineage, technical documentation, runbooks, recovery procedures, and definitions for critical datasets, transformations, and business rules.

Follow VPL security, privacy, governance, and compliance requirements and
assist with audit or customer-assurance evidence related to data processing.

Participate in after-hours
support for production-critical data processes after completing onboarding and demonstrating readiness.

Approximately 3–5 years of experience in data engineering, database development, business intelligence, analytics engineering, or a…