Senior Manager, Data Engineering

At Carrum, we are transforming how we pay for, deliver and experience healthcare. If you are passionate about changing healthcare and want to finally get rid of surprise bills, poor quality, and high prices, while thriving in an entrepreneurial, cutting-edge environment, we would love to connect with you.

In 2014 Carrum reinvented the Centers of Excellence (COE) category in digital health. Today, 95% of the US population lives within 50 miles of a Carrum COE and our providers rank in the top 10% nationally. Our team’s execution has been recognized by the venture community and we’ve raised more than $96M in aggregate from investors like OMERS, Tiger Global Management and Wildcat Ventures. Our impact has been externally proven in a 2021 RAND Corporation study and featured as a Harvard Business School (HBS) case study.

We are seeking an experienced and passionate Senior Data Engineering Manager to lead, mentor, and grow our Data Operations and Engineering team. The ideal candidate blends strong technical expertise in data engineering and the modern data stack with exceptional people management and cross-functional communication skills. You will be instrumental in defining our data standards, best practices, and overall data engineering roadmap. You’ve hustled, you’ve created, you’ve implemented, and you love the intensity of a startup in high-growth mode. 

This is a full time position, the salary range for this role is $190,000 - $220,000 depending on level of experience and geographic location.

Key Responsibilities

Team Management & Collaboration (50%)

• Team Development: Lead, mentor, and manage a team of Data Engineers, fostering a culture of ownership, continuous improvement, and technical excellence.
• Cross-Functional Partnering: Serve as the primary liaison between the Data Engineering team and other departments (Client Success, Partnerships, Product, Engineering, Clinical, and Business Intelligence) to translate business needs into technical requirements and roadmaps.
• Project Management: Work with leadership, stakeholders, and product managers to coordinate roadmap commitments, keep projects on track, and communicate and roll with changes as they inevitably occur
• Process Improvement: Drive the adoption of DevOps and DataOps methodologies, automating workflows, improving deployment processes, and reducing manual operational burden.

Data Operations, Security, & Compliance (25%)

• Operational Excellence: Oversee daily data operations of our Data Platform, including monitoring, incident response, and performance tuning of data pipelines and databases to ensure high uptime and meet defined SLAs.
• Data Quality & Governance: Implement proactive data quality checks and monitoring frameworks. Partner with stakeholders to establish and enforce data governance policies.
• HIPAA & Compliance: Ensure all data operations and infrastructure adhere strictly to healthcare regulatory requirements, including HIPAA and other relevant data privacy standards.
• Disaster Recovery: Develop and maintain robust backup, recovery, and business continuity plans for critical data assets.

Data Strategy & Engineering Leadership (25%)

• Architect and Build: Lead the design and implementation of scalable, reliable, and performant ETL/ELT data pipelines and data warehouse solutions that meet the demands of a growing organization.
• Multi-Cloud Infrastructure: Own and optimize the data infrastructure across AWS and Azure cloud environments, ensuring interoperability, cost efficiency, and robust security.
• Technology Expertise: Drive the selection and adoption of best-in-class data technologies, including modern data warehouses (e.g., Snowflake, Azure Synapse), orchestration tools (e.g., AWS Glue, Azure Data Factory), and real-time streaming solutions.
• Code Quality: Set and enforce standards for code quality, testing, version control (Git), and documentation for all data engineering projects.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field (Master’s preferred).
• 10+ years of experience in Data Engineering, with at least 2 years in a management or technical leadership role.
• Strong, hands-on experience with both AWS and Azure cloud platforms and their respective data services (e.g., AWS S3, EMR, Redshift, Lambda; Azure Data Lake, Azure Synapse, Data Factory).
• Expert proficiency in SQL, Python, and experience with modern data warehousing/data lake concepts.
• You are AI-native: You champion AI developer