Manager, Client Data Engineering

Abacus Insights; United States; On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive Leave & Benefits

Comprehensive health coverage

Equity for every employee

Growth-focused environment

Job summary

Abacus Insights is seeking a Manager, Client Data Engineering to guide a globally distributed team of 10–12 data engineers. You will bridge client delivery, technical execution, and people leadership, focusing on scalable data engineering practices and high-quality healthcare data integrations.

This hands-on leadership role requires deep expertise in ETL, data mapping, and complex data workflows, with strong Python/PySpark skills and experience working in AWS-based architectures.

Qualifications

• 7+ years of data engineering experience, including client-facing implementations.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• Demonstrated experience leading and mentoring technical teams.
• Strong hands-on design and support of ETL workflows and complex data integrations using Python and PySpark.

Responsibilities

• Lead client implementations end-to-end to ensure timely, high-quality delivery.
• Provide technical leadership across ETL, data mapping, and integration workflows.
• Improve CMS interoperability and related implementation processes.
• Coordinate with offshore and distributed teams to align priorities and maintain rigor.
• Mentor engineers and new hires, building a collaborative, performance-driven culture.
• Support delivery management, resource planning, and prioritization with delivery and product teams.
• Define team metrics, monitor progress, and drive continuous improvement.
• Promote adoption of tools and approaches that improve scalability and efficiency.

Skills

Data engineering

Client implementations

ETL workflows

Python

PySpark

AWS

Databricks

Snowflake

GitHub

GenAI

Education

Bachelor’s or Master’s in CS/Engineering/Data Science

Tools

Databricks

Snowflake

AWS

GitHub

GitLab

Job description

About Us

Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence.

We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we’re tackling big challenges in an industry that’s ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it’s why we are leading the way.

Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision.

Ready to make an impact? Join us and let’s build the future together.

About the Role

The Manager, Client Data Engineering is a key leader within our TechOps / Technical Implementation organization, leading a globally distributed team of approximately 10–12 data engineering professionals. This role bridges client delivery, technical execution, and people leadership, with a strong focus on successful client implementations and scalable, high-quality data engineering practices.

This hands‑on leadership role combines technical depth with operational discipline. The manager will guide feature delivery teams, partner with cross-functional stakeholders, and ensure reliable execution across complex healthcare data use cases, including ETL workflows, data mapping, and clinical data integration.

Your day to day

• Lead Client Implementations: Manage end-to-end client implementations, ensuring timely, high-quality delivery aligned with client expectations.
• Guide Data Engineering Execution: Provide technical leadership across ETL, data mapping, and integration workflows, promoting consistency and best practices.
• Optimize Interoperability Workflows: Work with stakeholders to improve CMS Interoperability and related implementation processes.
• Manage Global Teams: Partner with offshore and distributed teams to coordinate delivery, align priorities, and maintain operational rigor.
• Coach and Develop Talent: Mentor engineers and new hires while building a collaborative, performance-driven team culture.
• Own Operational Execution: Support delivery management, resource planning, and prioritization with delivery and product teams.
• Set and Track Performance Metrics: Define team success measures, monitor progress, and drive continuous improvement.
• Encourage Innovation: Promote practical adoption of tools, technologies, and approaches that improve scalability, quality, and efficiency.

What you bring to the team

• 7+ years of experience in data engineering roles, including client‑facing implementations.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Demonstrated experience leading and mentoring technical teams.
• Strong hands‑on experience designing and supporting ETL workflows and complex data integrations.Proficiency with Python and PySpark for data processing and transformation.
• Strong ability to write, optimize, and manage complex queries across large datasets.
• Experience working with AWS‑based architectures; familiarity with Databricks and Snowflake.
• Practical experience using GitHub or GitLab for code management and collaboration.
• Clear communicator with a data‑driven approach to solving complex technical and operational challenges.
• Experience working with GenAI and agentic development approaches.

What we would like to see, but not required

• Working knowledge of healthcare data environments and standards, including clinical or claims data, healthcare analytics, payer systems, or healthcare operations.
• Familiarity with data visualization tools such as Tableau or Power BI.
• Experience applying DevOps or CI/CD practices in data engineering environments.

What you’ll receive in return

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee, giving you a share in our success
• A growth-focused environment where your development matters

Work Arrangements

• Standard hours: 9 hours/day, 5 days/week
• Location: On-site
• Work hours: 10 AM–7 PM, with some variation based on business needs.

Our Commitment as an Equal Opportunity Employer

As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture—one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there’s anything we can do to support that—big or small—please let us know.

AI Use in Recruitment

We use AI-powered tools throughout our recruitment process. This includes Greenhouse's Real Talent Matching Technology, which helps prioritize applications based on job-related criteria, as well as additional AI tools used to support sourcing, interview preparation, and other recruiting tasks. We do not remove the human element—our recruiters and hiring teams review all applications and make all decisions related to candidate progression and hiring, regardless of which tools are used to support that process.

By applying, you acknowledge that we will collect and process your personal information for recruiting purposes in accordance with applicable data protection laws. Please review our Applicant Privacy Notice for more information, including your rights.