Manager, Data Engineering

Navitus Health Solutions

Manager, Data Engineering overseeing cloud-native data platforms at Archimedes. Leading integration and modernization of data ecosystems in a dynamic tech environment.

Posted 6/16/2026full-timeIdaho, Montana, Tennessee • 🇺🇸 United StatesSeniorLeadWebsite

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Hard Skills

data integrationdata architecturedata modelingETLAzure Databricksdata governancedata qualityCI/CDmachine learningpredictive analytics

Soft Skills

leadershipcoachingcollaborationcommunicationproblem-solvingperformance managementtraining developmentstrategic planningstakeholder engagementteam management

Tools & Technologies

SQL ServerAzureDatabricksdata lake houseETL toolsLinuxdata validation toolsmetadata management toolsdata integration platformsdata observability tools

Certifications & Qualifications

Bachelor's degree in computer scienceBachelor's degree in information systemsBachelor's degree in data science

Industry Keywords

healthcare datadata domainscanonical data modelsenterprise data productsdata integration policiesregulatory compliancedata accuracydata lineagedata dictionariesdata services processes

Tech Stack

Tools & technologies

AzureCloudETLLinuxPythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Benefits

Comp & perks

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!