MacroHealth is seeking a Data Engineering Team Lead to optimize healthcare delivery and payments using applied intelligence. The Data Foundation team needs a leader to design and implement high-quality data infrastructure, mentor team members, and contribute to the development of scalable SaaS and Analytics solutions.
Requirements
- Deep understanding of data architecture, pipelines, and distributed systems.
- Proficient in Python, and data engineering frameworks (e.g., Databricks, Spark, Airflow).
- Strong command of data modeling concepts (e.g., star/snowflake schemas, normalized/denormalized structures, dimensional modeling).
- Experience implementing and operationalizing data governance policies (e.g., data lineage, access control, data contracts).
- Familiarity with data cataloging and metadata management tools.
- Experience with modern big data technologies such as Databricks, Hadoop, Hive, Kafka etc.
- Experience designing and building solutions within a cloud-based microservice architecture.
Responsibilities
- Design and implement high quality, innovative and state of the art Data Infrastructure that complies with various compliance and follows industry best practice
- Actively participate in code and design reviews, mentoring, and helping craft and deliver performance reviews.
- Own architectural decisions for the core data foundation, including data modeling, storage layers, orchestration frameworks, and metadata management tools.
- Actively contribute to the design, development, and maintenance of scalable, production-grade data pipelines using modern technologies (e.g., Databricks, Airflow, Spark, Kafka).
- Lead the implementation of data platform components, including ingestion frameworks, transformation layers, orchestration systems, and observability tooling.
- Ensure high availability, reliability, and performance of data systems through monitoring, alerting, and operational best practices.
- Automate workflows to reduce manual overhead and increase developer productivity (e.g., data validation frameworks, schema enforcement, test automation).
Other
- Lead technical discussions, code reviews, and architecture planning sessions.
- Evaluate, select, and advocate for the right tools and technologies to support the data platform and ensure scalability and maintainability.
- Support data privacy and compliance efforts (e.g., HIPAA, SOC 2) by embedding governance into data workflows.
- Set standards for data quality, testing, version control, and deployment across all stages of the data lifecycle.
- Drive a culture of operational excellence through documentation, automation, and proactive monitoring.
- Lead, coach, and support a team of Data Engineers; providing regular feedback, and career development to support continuous learning.
- Establish clear ownership and ensure accountability for team deliverables and commitments
- Set team goals, conduct performance evaluations, and guide individual growth plans.
- Facilitate team meetings, drive sprint planning, and support agile delivery.
- Promote a culture of collaboration, continuous improvement, and psychological safety.
- Collaborate with engineering and product leadership to align Data Foundation team’s priorities with business and technical goals.
- Own team roadmap and project delivery timelines; translating business priorities into actionable technical plans and team backlogs.
- Continuously assess and optimize bottlenecks and opportunities to improve operational efficiency.
- Partner closely with product managers, data analysts, data engineers, and business stakeholders to understand data needs, pain points, and future use cases.
- Work with software engineers and platform application teams to define data contract boundaries, implement event-based data models, and establish reliable data sources.
- Serve as the technical liaison between data infrastructure and downstream data consumers, ensuring alignment on definitions, metrics, and SLAs.
- Help promote a data-as-a-product mindset by advocating for clear ownership, consistent standards, and high-quality data delivery across domains.
- Ability to establish and maintain standards for data quality, discoverability, and consistency.
- Proven ability to lead and mentor engineers; support their technical growth and performance.
- Experience operating in regulated environments with security and compliance needs.
- Proactive problem solver with a continuous improvement mindset.
- Bachelor’s degree in Computer Science or related field, or equivalent work experience.
- 7+ years of professional experience as a software developer or data engineer, ideally within the healthcare industry.
- 1+ years of formal leadership experience or serving in a Team Lead capacity to include leading code and design reviews, mentoring engineers, and helping craft and deliver performance reviews.
- A solid foundation in object-oriented languages.
- Experience in working with Product Management and other stakeholders to help define product direction and requirements. Demonstrated competence as a technical owner of large SaaS/IaaS systems spanning multiple components.
- Experience with healthcare data (e.g. health payments, authorizations, eligibility, electronic health records)
- Experience with existing and emerging health care interoperability technologies and standards (e.g. X12, NCPDP, FHIR)
- Experience working for or with healthcare providers/plans/payers particularly in data warehousing and business intelligence.
