AWS Databricks Data Engineer

AWS Data Engineer – Pharmacy/Life Sciences Data Platforms MustLocation: Boston, MA (3 days onsite)Duration: 6 months (possible extension)Client: DirectWe'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 DoBuild and tune data pipelines on Databricks (Spark, Delta Lake, Delta Live Tables) across a Bronze/Silver/Gold lakehouse setupStand up and support Seqera Platform (Nextflow Tower) environments, writing pipelines for genomics, imaging, and other compute-heavy scientific workloadsContainerize and orchestrate workflows using Docker/Kubernetes on AWSOwn the infrastructure-as-code (Terraform/CloudFormation) behind the platforms you buildWork directly with bioinformaticians, data scientists, and researchers to turn research computing needs into production-grade pipelinesKeep data quality, governance, and cataloging solid (Unity Catalog) as things scaleWhat You BringBachelor'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 & Spark2+ years running Seqera Platform / Nextflow pipelinesSolid AWS chops (S3, IAM, EC2, Lambda) and comfort in Python/SQLExperience in life sciences, pharma, biotech, or healthcare research settings is a strong plusCI/CD instincts (GitHub Actions, Jenkins, or similar) and an agile mindset