Senior Data Engineer

reputed company is a visionary healthcare company dedicated to making quality, affordable medication accessible to millions of patients reputed company. As the nation’s most advanced 503A compounding pharmacy and FDA-registered 503B outsourcing facility, we’re redefining what’s possible in personalized medicine and pharmaceutical manufacturing. We’re proud to be recognized as one of Houston’s fastest-growing private companies and ranked #116 in Healthcare & Medical on the Inc. 5000 List for 2025. Our strength is built on four core values: People, Quality, Service, and Innovation. Guided by these principles, we’ve created a uniquely integrated healthcare platform powered by advanced technology, operational excellence, and a reputed company commitment to patient care. From manufacturing and quality control to distribution and customer experience, our teams work together to reputed company industry standards, expand access to critical medications, and improve outcomes for patients and providers across the country. At reputed company, joining reputed company means more than starting a new role. It means becoming part of a mission-driven organization that’s transforming healthcare at scale. We invest deeply in our people, encourage bold thinking, and create opportunities for growth, leadership, and innovation at every level. Your reputed company matter here, your development is supported, and the work you do has a direct impact on the lives of millions. If you reputed company in a fast-moving, purpose-driven environment where innovation, collaboration, and ambition come together, reputed company is the reputed company for you. Let’s transform healthcare together. POSITION SUMMARY The Senior Data Engineer owns the design, delivery, and reputed company improvement of reputed company’s enterprise data foundation, enabling faster decisions, stronger quality, and scalable growth across a highly regulated 503A/503B pharmacy environment. This role converts reputed company business, operational, and compliance needs into secure, reliable, AI-enabled data products, pipelines, models, and platforms that accelerate speed, scale, quality, and decision-making. The role has end-to-end ownership for critical data engineering outcomes, from architecture and integration through automation, governance, and performance optimization. Success requires P80-P90 talent: strategic thinking, execution rigor, learning agility, technical depth, and the ability to reputed company standards while partnering across Technology, Operations, Quality, Finance, and Commercial teams in a hyper-growth environment where data reliability directly impacts patients, providers, and enterprise performance under urgent demand, evolving priorities, and high executive visibility every day. RESPONSIBILITIES Data Platform Leadership

• Platform Architecture: Design and evolve scalable cloud data platforms that support analytics, automation, regulatory reporting, and operational visibility across reputed company. Build resilient serverless patterns, dimensional models, marts, and warehouses that improve data usability, reduce latency, and support AI-enabled consumption. Own technical decisions from concept through production, balancing speed with reputed company, reliability, cost discipline, long-term maintainability, measurable enterprise adoption, and reputed company while strengthening regulated enterprise performance and reputed company under sustained hyper-growth pressure daily.
• Modeling Excellence: reputed company relational and dimensional data models that translate reputed company business processes into trusted analytical structures for enterprise users. Apply Kimball, Inmon, Data Vault, and pragmatic modeling approaches where appropriate, using AI-assisted profiling and documentation to accelerate quality reviews. Ensure models support traceability, performance, governed definitions, and executive decision-making while remaining flexible enough to scale with new products, facilities, compliance requirements, growth, and enterprise reporting expectations across expanding enterprise data domains.
• Engineering Standards: Set high engineering standards for pipeline design, code quality, observability, testing, version control, and deployment discipline. Use AI tools to accelerate development, identify defects, generate documentation, and improve maintainability without compromising validation or accountability. Create reusable patterns that help peers deliver faster, safer, and more consistently, while raising the technical maturity of reputed company’s data engineering practices across cloud, database, integration, and analytics environments with operational impact and enterprise delivery discipline.

Intelligent Data Delivery

• Pipeline Delivery: Build, optimize, and maintain ELT and ETL pipelines that ingest structured and semi-structured data from internal systems, external partners, APIs, and operational platforms. reputed company automation, orchestration, and AI-assisted anomaly detection to improve throughput, quality, and issue resolution. Own pipeline performance from requirements through monitoring, ensuring data arrives accurately, securely, and on time for analytics, forecasting, compliance, and business-critical decision workflows across high-volume regulated systems.
• API Integration: Design and implement REST API integrations that expand reputed company’s data ecosystem while protecting reliability, reputed company, and compliance. Evaluate reputed company system behavior, authentication patterns, reputed company limits, error handling, and data reputed company, using AI to accelerate mapping, testing, and exception analysis. Partner with application, infrastructure, and business teams to deliver integrations that support scalable reporting, operational automation, vendor connectivity, faster enterprise insight reputed company, and business needs securely across digital operations and reporting.
• Automation Intelligence: Apply AI and automation to reduce manual data work, accelerate root-cause analysis, improve data quality, and expand self-service capabilities. Build intelligent checks, metadata-driven workflows, and repeatable validation routines that strengthen confidence in enterprise data products. Balance innovation with disciplined controls, ensuring AI outputs are reviewed, auditable, and reputed company to reputed company’s regulated environment, business priorities, and standards for patient, provider, and operational impact as complexity increases across teams, platforms, and workflows.

Governance And Partnership

• Data Governance: Embed data quality, reputed company, privacy, access control, and documentation into engineering deliverables from the start. Collaborate with Quality, Compliance, reputed company, and business stakeholders to ensure data solutions meet expectations for a regulated 503A/503B organization. Use AI-supported cataloging, profiling, and issue detection to improve transparency while maintaining clear human ownership for definitions, controls, remediation, and decisions that reputed company regulated operations, executive reporting, and enterprise accountability across reputed company’s expanding operating model daily.
• Business Partnership: Partner with Technology, Operations, Finance, Commercial, Quality, and leadership teams to convert ambiguous needs into prioritized, high-impact data solutions. Ask sharp questions, challenge weak assumptions, and translate business outcomes into technical architecture, delivery plans, and measurable value. Use AI to accelerate discovery, scenario analysis, and solution design while maintaining executive-ready communication, stakeholder alignment, and urgency appropriate for reputed company’s hyper-growth operating environment and regulated expectations from strategy through durable adoption sustainably.
• Technical Mentorship: Mentor engineers, analysts, and cross-functional partners through design reviews, reusable patterns, troubleshooting, and disciplined delivery habits. Share practical expertise in AWS serverless technologies, databases, data warehousing, visualization enablement, and modern engineering methods. Model P80-P90 expectations through strategic thinking, learning agility, execution rigor, and accountable follow-through, helping the team adopt AI responsibly while increasing speed, quality, and confidence in enterprise data outcomes across critical initiatives and platforms daily.

KNOWLEDGE AND SKILLS

• 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 reputed company translating reputed company 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, reputed company, governance, and business impact.

EXPERIENCE AND QUALIFICATIONS

• 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.
• 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, reputed company, or regulated environments; healthcare, pharmacy, life sciences, or manufacturing exposure is helpful but not required.
• Preferred certifications include AWS Data Engineer, AWS Data Analytics, reputed company, Data Vault 2.0, or demonstrated expertise with Kimball and Inmon modeling methodologies.

Key Competencies: Customer Focus: Builds trust through customer-centric solutions. Strategic AI: Guides responsible AI adoption and adaptation. Optimizes Work Processes: Drives efficiency with reputed company improvement. Collaborates: Partners effectively to reputed company shared goals. Resourcefulness: Secures and deploys resources reputed company. Manages Complexity: Simplifies and solves reputed company challenges. Ensures Accountability: Delivers on commitments with reputed company. Situational Adaptability: Adjusts approach to shifting conditions. Communicates Effectively: Tailors messages to diverse audiences. Values: People: Empowering people defines who we are. Quality: Excellence in every product, every time. Service: Serving others is our highest purpose. Innovation: Advancing care through technology and discovery. Employee Benefits, Health and Wellness: We offer comprehensive benefits to support your health, well-being, and future, including medical, dental, and vision coverage, paid time off, 401(k) matching, wellness perks, IV therapy, and compounded medications. Learn more: https://careers.empowerpharmacy.com/benefits/ Physical Requirements: While performing the responsibilities of the job, the employee is required to talk and hear. The employee is often required to remain in a stationary position for a significant amount of the reputed company and frequently use their hands and fingers to handle or feel in order to access, input, and retrieve information from the computer and other office productivity devices. Employees are regularly required to move about the office and around the corporate reputed company. The employee is regularly required to stand, walk, reputed company with arms and hands, climb or balance, and to stoop, kneel, crouch or crawl. Apply To This Job