Note: The job is a remote job and is open to candidates in USA. Harnham is recruiting for an unnamed healthcare technology organization developing SaaS analytics and workflow solutions for public-sector healthcare organizations. The Data Engineering Manager will lead and develop the Data Engineering team, set technical direction, and remain hands-on with complex engineering work. The role focuses on customer data onboarding, scalable reusable data capabilities, and platform modernization.
Responsibilities
- Provide technical direction across data architecture, solution design, data modeling, ELT, automation, and data quality
- Remain hands-on with complex engineering initiatives and help resolve difficult technical challenges
- Lead the development of scalable, reusable data processing capabilities
- Drive modernization of existing data architectures and engineering practices
- Evaluate emerging technologies, including AI-assisted tools that improve data processing, quality, and engineering productivity
- Establish engineering standards, documentation practices, and technical design processes
- Guide architectural decisions while clearly communicating assumptions, alternatives, tradeoffs, and recommendations
- Lead the design and optimization of data pipelines, transformations, and standardized data models
- Own the day-to-day execution and effectiveness of the Data Engineering function
- Translate customer, product, and engineering priorities into actionable plans and resource allocation
- Balance customer data onboarding, platform development, modernization, and technical debt
- Manage multiple concurrent engineering initiatives, including dependencies, delivery commitments, and competing priorities
- Establish visibility into engineering capacity, timelines, risks, and delivery status
- Partner with Product, Engineering, Customer Success, and leadership to align technical priorities with business needs
- Develop and maintain a technical roadmap that addresses recurring customer and product requirements
- Lead, coach, and develop an experienced team of Data Engineers
- Establish clear performance expectations and provide ongoing feedback and career development
- Support hiring, onboarding, mentoring, and knowledge sharing
- Identify technical skill gaps and resource constraints
- Build a culture of accountability, collaboration, technical rigor, and continuous improvement
- Raise the team's overall engineering capability through strong technical leadership and effective management practices
Skills
- Must be legally authorized to work in the U.S. without employer sponsorship
- 12+ years of relevant engineering experience
- 5+ years of direct engineering management experience
- Proven experience managing a Data Engineering function, including people, priorities, resources, processes, and delivery
- Deep hands-on Data Engineering experience with SQL and Python
- Strong experience designing and building scalable ELT pipelines, transformations, and data models
- Experience across relational databases, MPP platforms, and file-based data architectures
- Hands-on experience with modern orchestration and transformation frameworks such as Airflow, Astronomer, Dagster, dbt, or Windmill
- Experience operating, monitoring, and optimizing production data pipelines
- Experience integrating complex datasets from multiple sources into standardized data models
- Strong data profiling, validation, quality monitoring, and automation experience
- Experience designing automated data quality capabilities that measure completeness, consistency, density, and data gaps
- Proven ability to lead data platform modernization and architectural transformation
- Experience migrating legacy relational database-centric environments toward distributed, file-based, or cloud-native architectures
- Experience applying AI-assisted technologies to improve Data Engineering workflows, automation, data quality, or productivity
- Strong architectural judgment and the ability to evaluate technical alternatives
- Experience establishing engineering standards and guiding complex technical decisions
- Experience developing technical roadmaps and balancing competing engineering priorities
- Experience working across multiple engineering environments, organizations, or stages of growth
- Healthcare data experience
- Strong communication skills and the ability to explain technical tradeoffs to both engineering teams and business leadership
- Bachelor's degree in Computer Science or a related field, or equivalent experience
- The ideal candidate has progressed from a strong hands-on engineering background into leadership but has maintained the technical depth required to challenge architectural decisions, solve difficult problems, and personally contribute when necessary
- The strongest candidates will combine three capabilities that are not always found together: deep hands-on Data Engineering expertise, experienced people leadership, and the ability to modernize a data platform while maintaining reliable day-to-day delivery
- You should be equally comfortable reviewing architecture, helping an engineer solve a difficult pipeline problem, managing competing delivery priorities, and coaching experienced technical professionals
- You'll understand how to move beyond one-off customer integrations toward reusable engineering capabilities that improve scalability, consistency, and operational efficiency
- You'll also bring the judgment to determine when existing technologies and processes should be improved, when they should be replaced, and how to introduce modernization without disrupting customer commitments
- Healthcare data experience is important because the role requires an understanding of complex source systems, data quality challenges, and the relationship between technical solutions and real-world healthcare use cases
Benefits
- 100% Remote
- Medical, dental, and vision insurance
- Company-paid life and disability insurance
- A 401(k) with company match
- A vacation travel stipend
- Generous paid time off
Company Overview