Lead Data Engineer (Remote)

8th Light is a technology solutions consultancy that partners with organizations to solve complex software challenges and deliver durable results. The Lead Data Engineer will own the data layer of client engagements, designing scalable pipelines and schemas, leading architecture and modeling discussions, and mentoring teammates while collaborating closely with clients.

Responsibilities:

• Making immediate contributions to projects and rapidly building trust with clients
• Designing and building data pipelines and schemas that hold up as data volume and complexity grow
• Leading data architecture and modeling discussions, weighing tradeoffs and documenting the reasoning
• Working pragmatically to balance technology choices while delivering high-quality work within deadlines
• Generating new solutions to technical and non-technical challenges alongside teammates and clients
• Leading or initiating retrospectives and feedback conversations with teams and clients
• Clearly articulating and documenting outcomes and driving action items forward
• Contributing to the health of your team and 8th Light's culture by modeling our Values
• Maintaining relationships with client technical leaders
• Identifying, mitigating, and resolving blockers to team progress
• Contributing to 8th Light by mentoring, leading workshops, representing us in the tech community, or supporting our hiring process

Requirements:

• You've built a track record of data engineering work others rely on, typically over the course of 6 or more years
• • Designed and built scalable data pipelines that ingest, transform, and move data from sources like EHRs, claims, APIs, and CRMs
• • Worked hands-on with at least one cloud data platform (Snowflake, Databricks, Azure Data Factory, AWS Redshift, or Google BigQuery)
• • Written and tuned production SQL, including query optimization and debugging
• • Used Python or another language like Scala or Java to automate data workflows
• • Applied ETL/ELT principles, data warehousing, and data modeling to real client problems
• • Delivered projects on AWS, Azure, or GCP
• • Picked up new and unfamiliar tools quickly, treating unknown challenges as part of the work rather than a blocker
• • Shipped high-quality, maintainable software collaboratively and incrementally, tailored to the needs of the clients you've served
• • Collaborated with teams using Git and CI/CD
• • Communicated clearly with technical and non-technical stakeholders about data decisions and tradeoffs
• • Mentored teammates and shared what you know
• • Actively sought out and given feedback
• • Healthcare data: Epic, HL7, FHIR, and claims
• • CI/CD pipelines, Git, and DevOps workflows
• • Infrastructure as Code with tools like Terraform or CloudFormation
• • Real-time and streaming data tools such as Kafka, Kinesis, or Pub/Sub
• • Containerization with Docker and Kubernetes
• • Cloud or data platform certifications