[Remote] Lead Data Engineer
Note: The job is a remote job and is open to candidates in USA. Harnham is hiring a Lead Data Engineer to lead the team responsible for the data platform supporting healthcare analytics products and internal reporting. The role combines people leadership with hands-on engineering across ELT pipelines, data modeling, platform reliability, observability, and governance, while partnering with product, analytics, engineering, and healthcare stakeholders.
Responsibilities
- Lead, mentor, and set technical standards for a data engineering team
- Build and maintain ELT pipelines using Python, SQL, dbt, and Airflow; Dagster or Astronomer experience is also relevant
- Develop reliable ingestion and transformation workflows for healthcare and transactional data
- Design and optimize data models, curated tables, and reusable dbt models
- Work extensively with PostgreSQL and contribute to data architecture decisions
- Improve data quality, lineage, monitoring, alerting, documentation, and incident response
- Optimize pipeline performance, scalability, reliability, and cost
- Establish standards for testing, deployment, security, version control, and data governance
- Contribute directly to development and long-term platform strategy
Skills
- Must be authorized to work in the U.S.; no visa sponsorship or transfers available
- 5+ years of experience in data engineering, analytics engineering, software engineering, or a related field
- 1+ year leading, mentoring, or serving as a technical lead for data engineers
- Strong production Python and advanced SQL skills
- Hands-on dbt experience, including models, tests, documentation, and deployments
- Experience with Airflow; Dagster and/or Astronomer are also considered
- Strong PostgreSQL experience, including schema design and query tuning
- Experience designing and operating ELT pipelines
- Experience working with transactional data, such as claims, billing, enrollment, payments, or application events
- Healthcare-data experience and familiarity with its privacy, quality, and governance requirements
- Working knowledge of MPP database concepts, including distributed query processing, partitioning, and performance at scale
- Experience with Snowflake, Redshift, BigQuery, Databricks, or Azure Synapse
- Healthcare domain exposure: claims, clinical, provider, member, payer, pharmacy, eligibility, or revenue-cycle data
- Experience with HIPAA-regulated or other sensitive data
- Familiarity with observability, lineage, cataloging, governance, or data-quality tools
- Exposure to CI/CD, infrastructure as code, containers, or cloud-native data platforms
- Experience building self-service data products in a SaaS, analytics, healthcare-tech, or growth-stage environment
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