Company
Archimedes Pay Range
USD $0.00 - USD $0.00 /Yr. STAR Bonus % (At Risk Maximum)
0.00 - Ineligible Work Schedule Description (e.g. M-F 8am to 5pm)
Core Business Hours- Remote or Hybrid 3 Days in Office from our St. Louis, MO or Brentwood, TN offices Remote Work Notification
ATTENTION: Archimedes is unable to offer remote work to residents of Alaska, Arizona, Arkansas, California, Connecticut, Delaware, Hawaii, Idaho, Louisiana, Maine, Massachusetts, Michigan, Mississippi, Montana, Nebraska, Nevada, New Mexico, New York, North Carolina, North Dakota, Oregon, Rhode Island, South Carolina, South Dakota, Texas, Utah, Vermont, Washington, West Virginia, And Wyoming. Overview

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, DataOps, 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 DataOps 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, DevOps, 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.

Responsibilities

How do I make an impact on my team?

• 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 DataOps 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 the current data services processes, identify challenges, quantify the business value, establish procedures to address challenges, and support the future state model and vision definition.
• Stay current with industry trends and advancements in data integration and management technologies.
• Lead healthcare data integration initiatives involving claims, eligibility, pharmacy, clinical, financial, operational, and partner data sources.
• Serve as technical authority for data modeling, canonicalization, master data management, and enterprise data governance practices.
• Provide direct leadership, coaching, hiring, and performance management for Data Engineers and Data Integration Engineers.
• Participate in architecture reviews and remain actively engaged in solution design, platform modernization, and technical delivery.
• Develop training plans to foster growth and development across functional areas to meet expanding technology needs. Research and develop learning needs for ongoing system developments with contractors.
• Continuously review and monitor technology resources and gap analysis, establish criteria and make recommendations for advancement.
• Develop and implement a comprehensive data management strategy aligned with strategic objectives. Establish resources, tools and direction for each functional leader.
• Establish data integration policies and procedures to ensure data accuracy, security, and compliance with regulatory requirements.
• Participate in, adhere to, and support compliance, people and culture, and learning programs.
• Perform other duties as assigned.

Qualifications

What our team expects from you?

• Education: Bachelor’s degree in the field of computer science, information systems, or data science required.

• Experience:
  • 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, Data Integration, or Data Platform Engineering required.
  • 5+ years leading Data Engineering teams required.
  • Experience designing and implementing Databricks Lakehouse architecture required.
  • Experience establishing canonical data models, enterprise data products, metadata management, and governance frameworks required.
  • Experience supporting AI, machine learning, analytics, and automation initiatives through modern data engineering practices required.
  • Experience modernizing legacy ETL and SQL-based architectures into cloud-native platforms required.
  • Experience with healthcare data domains strongly preferred.
  • Advanced experience and skills in data ingestion, data architecture, and data integration techniques required.
  • Proficiency in data integration tools and languages (e.g., SQL, Linux, Python, ETL tool) required.

 

What can you expect from Archimedes? 

• Top of the industry benefits for Health, Dental, and Vision insurance 
• 20 days paid time off 
• 4 weeks paid parental leave 
• 9 paid holidays 
• 401K company match of up to 5% - No vesting requirement 
• Adoption Assistance Program 
• Flexible Spending Account 
• Educational Assistance Plan and Professional Membership assistance 
• Referral Bonus Program – up to $750! 

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