Manager, Data Engineering

Manager, Data Engineering

Archimedes
- Transforming the Specialty Drug Benefit
- Archimedes is the industry leader in specialty drug management solutions. Founded with the goal of transforming the PBM industry to provide the necessary ingredients for the sustainability of the prescription drug benefit – alignment, value and transparency – Archimedes achieves superior results for clients by eliminating tightly held PBM conflicts of interest including drug spread, rebate retention and pharmacy ownership and delivering the most rigorous clinical management at the lowest net cost.

We are committed to providing equal employment opportunity to all applicants and employees and comply with all applicable nondiscrimination regulations, including those related to protected veterans and individuals with disabilities. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, or handicap.

The Manager, Data Engineering is responsible for leading the design, implementation, operation, and modernization of the organization's enterprise data platform, lakehouse architecture, data integration ecosystem, and AI-ready data foundation. This role provides both technical leadership and people leadership across Data Engineering, Data Integration, Data Ops, and enterprise data modernization initiatives. Operating within an Azure-first, Databricks-centric environment, the Manager, Data Engineering leads the organization's transition from traditional SQL-centric ETL architectures toward modern cloud-native lakehouse platforms utilizing Azure Databricks, Delta Lake, Unity Catalog, Azure Data Lake Storage Gen2, Azure Data Factory, APIs, event-driven architectures, and modern Data Ops practices.

This is a hands-on leadership role responsible for establishing enterprise data architecture standards, canonical data models, master data management strategies, data governance controls, data quality frameworks, integration patterns, and AI-ready data products supporting analytics, machine learning, intelligent automation, robotic process automation (RPA), generative AI, and operational decision-making.

The Manager, Data Engineering directly leads Data Engineers and Data Integration Engineers while remaining actively engaged in architecture, design reviews, platform modernization, solution delivery, and technical mentoring. The role partners closely with Software Engineering, Cloud Engineering, Dev Ops, Security, Analytics, Compliance, and business stakeholders to deliver scalable, secure, governed, and reusable enterprise data assets. The Manager, Data Engineering is accountable for both current-state ETL and integration operations as well as the long-term transformation toward cloud-native data platforms, lake house architectures, enterprise data products, and AI-enabled business capabilities.

• Lead and support the organizational data integration efforts by effectively developing and leading a team of data integration developers, engineers, architects, and managers.
• Establish enterprise data architecture standards, canonical data models, data domains, and data product strategies.
• Lead the modernization of legacy SQL Server ETL workloads into Azure Databricks and Lakehouse architectures.
• Define and govern Bronze, Silver, and Gold data layer standards.
• Establish enterprise data dictionaries, business glossaries, metadata management, and lineage standards.
• Lead development of AI-ready data products supporting machine learning, predictive analytics, intelligent automation, RAG, and agentic AI solutions.
• Define enterprise Data Ops practices including CI/CD, automated testing, observability, data quality, and deployment automation.
• Lead the design and implementation of data integration and data lake house solutions.
• Lead collaboration efforts with IT teams to ensure robust and scalable data architecture is established and meeting company objectives.
• Lead the establishment of data validation and reconciliation processes to maintain data accuracy.
• Partner with business stakeholders to understand data requirements and deliver solutions that meet their needs.
• Assess…