Senior Data Engineer

Empower Pharmacy is a visionary healthcare company dedicated to making quality, affordable medication accessible to millions of patients nationwide. The Senior Data Engineer owns the design, delivery, and continuous improvement of Empower’s enterprise data foundation, enabling faster decisions and scalable growth across a highly regulated pharmacy environment.

Responsibilities:

• Design and evolve scalable cloud data platforms that support analytics, automation, regulatory reporting, and operational visibility across Empower
• Develop relational and dimensional data models that translate complex business processes into trusted analytical structures for enterprise users
• Set high engineering standards for pipeline design, code quality, observability, testing, version control, and deployment discipline
• Build, optimize, and maintain ELT and ETL pipelines that ingest structured and semi-structured data from internal systems, external partners, APIs, and operational platforms
• Design and implement REST API integrations that expand Empower’s data ecosystem while protecting reliability, security, and compliance
• Apply AI and automation to reduce manual data work, accelerate root-cause analysis, improve data quality, and expand self-service capabilities
• Embed data quality, lineage, privacy, access control, and documentation into engineering deliverables from the start
• Partner with Technology, Operations, Finance, Commercial, Quality, and leadership teams to convert ambiguous needs into prioritized, high-impact data solutions
• Mentor engineers, analysts, and cross-functional partners through design reviews, reusable patterns, troubleshooting, and disciplined delivery habits

Requirements:

• Minimum 8 years of experience in data engineering, including hands-on ownership of cloud data platforms, data modeling, data warehousing, pipeline development, and enterprise data integration
• Bachelor's degree in Computer Science, Statistics, Informatics, Information Systems, Engineering, or another quantitative discipline; equivalent depth of experience may be considered
• Advanced proficiency in AWS serverless data services, relational and non-relational databases, data warehousing, dimensional modeling, ELT and ETL orchestration, REST APIs, and production-grade engineering practices
• Strong ability to apply AI-assisted development, profiling, testing, documentation, anomaly detection, and workflow automation while maintaining human review, validation discipline, and regulated-environment accountability
• Demonstrated skill translating complex operational, financial, quality, and commercial requirements into scalable data models, pipelines, reporting foundations, and executive-ready technical recommendations
• High learning agility, collaboration, communication, project ownership, and problem-solving capability, with the judgment to balance speed, quality, security, governance, and business impact
• Deep experience with AWS serverless technologies, SQL, Python or comparable programming languages, relational and non-relational databases, ELT and ETL tools, visualization enablement, and production support
• Experience designing governed data solutions in fast-paced, complex, or regulated environments; healthcare, pharmacy, life sciences, or manufacturing exposure is helpful but not required
• Preferred certifications include AWS Data Engineer, AWS Data Analytics, Snowflake, Data Vault 2.0, or demonstrated expertise with Kimball and Inmon modeling methodologies