AWS Databricks Data Engineer

AWS Data Engineer – Pharmacy/Life Sciences Data Platforms Must

Location: Boston, MA (3 days onsite)

Duration: 6 months (possible extension)

Client: Direct

We're looking for a data engineer who's just as comfortable tuning a Spark pipeline as they are standing up a Nextflow workflow for a genomics or imaging use case. This role sits at the intersection of cloud data engineering and scientific computing - you'll be building the data backbone that lets our researchers go from raw scientific data to real insight without the usual friction.

What You'll Do

• Build and tune data pipelines on Databricks (Spark, Delta Lake , Delta Live Tables) across a Bronze/Silver/Gold lakehouse setup
• Stand up and support Seqera Platform (Nextflow Tower) environments, writing pipelines for genomics, imaging, and other compute-heavy scientific workloads
• Containerize and orchestrate workflows using Docker/Kubernetes on AWS
• Own the infrastructure-as-code (Terraform/CloudFormation) behind the platforms you build
• Work directly with bioinformaticians, data scientists, and researchers to turn research computing needs into production-grade pipelines
• Keep data quality, governance, and cataloging solid (Unity Catalog) as things scale

What You Bring

• Bachelor's degree in Computer Science, Data Engineering, Bioinformatics, or a related technical field (Master's a plus)
• 5+ years in data or cloud engineering, including 3+ years hands-on with Databricks & Spark
• 2+ years running Seqera Platform / Nextflow pipelines
• Solid AWS chops (S3, IAM, EC2, Lambda) and comfort in Python/SQL
• Experience in life sciences , pharma , biotech, or healthcare research settings is a strong plus
• CI/CD instincts (GitHub Actions, Jenkins, or similar) and an agile mindset