• Design, implement, and maintain complex data pipelines, ensuring scalability and reliability using Airflow, dbt, Rivery, Python, and SQL, enabling robust ingestion and transformation of structured and semi-structured data. • Serve as a strategic partner to business teams, working closely with stakeholders to translate high-level goals into data solutions that support forecasting, performance tracking, and optimization. • Develop and maintain clean, well-documented data models in Snowflake and BigQuery that support analytics, reporting, and operational workflows and contribute to architecture decisions. • Integrate data from a variety of internal and external sources, including Google Analytics and third-party APIs, to support full-funnel visibility across departments. • Enable self-service analytics by ensuring data assets are discoverable and usable via tools such as Tableau, including thoughtful semantic layer design and performance tuning. • Contribute to the development of robust monitoring and observability practices for data quality and pipeline health. • Collaborate on architecture and design decisions, including cloud infrastructure and containerization using AWS, Pulumi, and Docker. • Maintain strong documentation and promote engineering standards that ensure transparency, maintainability, and reusability of data systems.

Principal Data Engineer EmpiRx Health is the leading clinically-driven pharmacy benefits management company. As the pioneer in value-based pharmacy care, EmpiRx Health puts its customers and members first by enabling them to take control of their pharmacy benefits, healthcare outcomes, and financial results. We place more emphasis on member care than any other PBM by focusing on health outcomes first. Our pharmacists and clinicians are at the center of everything we do―and our population health solution delivers tailored strategies for our clients. Leveraging our newly launched, AI-powered pharmacy care platform, Clinically™, EmpiRx Health’s pharmacists and client experience teams provide the highest quality pharmacy care to our clients and their members. This enables benefits plan sponsors to keep their members healthy, happy, and productive, while substantially reducing prescription drug spending, which has been on an explosive growth trajectory in recent years. EmpiRx Health is in unprecedented growth The Principal Data Engineer is a senior, hands-on technical leader responsible for designing, building, and evolving EmpiRx Health’s finance-critical data ecosystem. This role works cross-functionally with engineering, finance, product, and business leaders while remaining deeply embedded within a small, agile delivery team supporting our Finance organization. The role plays a key part in improving team agility, delivery discipline, and overall execution effectiveness. This position balances direct technical ownership of mission-critical financial data pipelines while collaborating with cross-functional leadership to define data architecture, establish engineering standards, and drive engineering excellence, ensuring data solutions are accurate, scalable, reliable, and tightly aligned with business outcomes. Key Responsibilities: Rec Technical Leadership & Architecture - Own the technical direction of finance-centric data engineering solutions, with deep responsibility for Databricks and Oracle based integrations. - Lead the design and evolution of scalable ELT/ETL pipelines and data platforms using Databricks and Python. - Help define and uphold data engineering standards, patterns, and best practices across the organization. - Make architectural decisions that balance long-term platform health with practical delivery constraints. - Advance organizational data maturity through improvements in reliability, observability, and platform discipline. Delivery & Execution - Operate as a senior individual contributor, leading by example through daily hands-on design, implementation, problem solving, and technical decision-making. - Actively contributes to improving team agility, delivery flow, and execution discipline by strengthening engineering practices, technical hygiene, and collaboration. - Partner with Product Owners and Scrum Masters to identify delivery impediments, reduce friction, and continuously improve how the team plans, executes, and ships work. - Own the end-to-end lifecycle of finance-critical data pipelines, including ingestion, transformation, validation, delivery, and operational support. - Design and build robust, scalable integrations between Databricks, Oracle, and downstream platforms supporting finance, operations, and client deliverables. - Ensure the production of high-quality, compliant data extracts for internal teams, clients, vendors, and partners. - Continuously monitor data reliability, performance, and quality; proactively identify risks and drive corrective actions. - Serve as a primary technical partner to Finance and business stakeholders, translating complex requirements into effective, maintainable solutions. - Contribute directly to sprint execution within a small agile delivery team while also shaping broader data engineering practices across the organization. Collaboration & Influence - Work closely with Finance leadership and business partners to understand requirements, translate needs into technical solutions, and drive adoption. - Collaborate with data engineering leadership, application engineering, analytics, and product teams to ensure data solutions are aligned with platform strategy and business goals. - Mentor and guide engineers through technical leadership, knowledge sharing, and architectural coaching (without direct people management responsibility). - Contribute to cross-team alignment on data modeling, integration patterns, and platform evolution. Required Qualifications & Experience: - Bachelor’s degree in computer science or related field. - 10+ years of professional experience in data engineering or related roles. - 3+ years of hands-on experience building solutions in Databricks using Python and notebooks. - Strong experience integrating with Oracle and other RDBMS platforms. - Proven ownership of complex data pipelines and business-critical integrations. - Demonstrated ability to operate as a senior individual contributor with broad organizational influence. - Excellent communication, collaboration, and stakeholder-engagement skills. - Strong analytical, problem-solving, and execution discipline. Preferred Qualifications: - Experience supporting financial systems and enterprise finance organizations. - Healthcare or PBM domain experience. - Expertise with Delta Lake, data modeling, data quality frameworks, and data observability patterns Work Environment: Remote Benefits And Perks Subject to program eligibility, this position qualifies for a robust suite of benefits including Paid Time Off, a 401(k) program, Health Insurance including Dental & Vision coverage, Student Loan Reimbursement, Health Savings Account, and an Employee Assistance Program. EmpiRx Health is an Equal Opportunity Employer At EmpiRx Health, we wholeheartedly embrace the power of diversity and the magic of inclusion. The kaleidoscope of unique perspectives, backgrounds, and talents fuels our innovation and sets us apart. We're on a mission to build a team as diverse as the world we serve, where everyone is welcome and celebrated. We're not just breaking down barriers; we're actively erasing them to create an environment where opportunity knows no bounds. In unity, we find our strength and invite individuals from all walks of life to join us in our exhilarating journey to shape a brighter, more inclusive future together. Note: This job description is a general outline of responsibilities and qualifications for the role. Additional duties may be assigned, and the position may evolve to meet the organization's needs

• Design, build, and maintain robust cloud infrastructure • Develop and optimize automated data pipelines • Integrate data from various sources into BigQuery • Monitor, maintain, and optimize data workflows • Document workflows and improve processes

• Analyze clinical data, identify and report trends. • Design and build modern data-centric software applications for healthcare processes. • Build data pipelines and transformations, data enrichment processes. • Mentor and assist less experienced Data Engineers. • Collaborate with Product, Platform, and Architecture teams for joint efforts.