Data Engineer

Duration : 12 - months contract (high possibility of extension) Location : Cambridge MA Job Requirement We are seeking a highly skilled Data Engineer with expertise in Databricks, Seqera Platform (Nextflow Tower), cloud data engineering, and scientific data workflows to support our Discovery R&D and data science initiatives. The ideal candidate will design, develop, and maintain scalable data platforms and automated bioinformatics/data science pipelines that enable researchers and scientists to efficiently process, analyze, and access large-scale scientific and business datasets. This role requires strong experience in cloud-native architectures, data engineering best practices, workflow orchestration, and collaboration with cross-functional teams including scientists, bioinformaticians, data scientists, and IT infrastructure teams. About the Role The role involves designing, developing, and maintaining scalable data platforms and automated bioinformatics/data science pipelines. Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and cloud-native technologies. Build and optimize ETL/ELT processes for structured, semi-structured, and unstructured data. Develop data ingestion frameworks for research, laboratory, clinical, and external scientific datasets. Implement data quality, validation, monitoring, and governance processes. Support enterprise data lakehouse architecture and data platform modernization initiatives. Databricks Administration & Development Develop and maintain Databricks notebooks, workflows, Delta Live Tables, and Jobs. Create optimized Spark-based transformations and data processing solutions. Implement Medallion Architecture (Bronze, Silver, Gold) for data lifecycle management. Manage Delta Lake environments and optimize performance, scalability, and cost. Integrate Databricks with cloud-native services and enterprise applications. Seqera Platform & Scientific Workflow Management Deploy, configure, and support Seqera Platform (formerly Nextflow Tower). Develop and maintain Nextflow pipelines for bioinformatics, genomics, imaging, AI/ML, and scientific computing workloads. Integrate Seqera workflows with AWS cloud infrastructure and compute environments. Support containerized workflows using Docker and Kubernetes technologies. Enable reproducible, scalable, and compliant scientific data processing workflows. Design and implement cloud-based data solutions in AWS. Manage cloud storage solutions including S3 and data lifecycle policies. Develop Infrastructure-as-Code solutions using Terraform or CloudFormation. Implement security controls and access management following enterprise IT standards. Partner with data scientists, researchers, bioinformaticians, and business stakeholders to understand data requirements. Provide technical guidance on data engineering best practices and workflow automation. Troubleshoot pipeline failures, performance issues, and workflow bottlenecks. Contribute to platform roadmaps and continuous improvement initiatives. Maintain technical documentation, SOPs, and knowledge articles. Qualifications Education Bachelor's degree in Computer Science, Information Technology, Data Engineering, Bioinformatics, or a related technical field. Master's degree preferred. Experience 5+ years of experience in data engineering, cloud engineering, or analytics platform development. 3+ years of hands-on experience with Databricks and Apache Spark. 2+ years of experience with Seqera Platform (Nextflow Tower) and Nextflow workflows. Experience supporting scientific research, life sciences, pharmaceutical, biotech, or healthcare environments preferred. Required Skills Databricks & Data Engineering, Databricks Lakehouse Platform Apache Spark (PySpark, Spark SQL) Databricks Workflows Unity Catalog SQL and Python Seqera & Scientific Computing; Seqera Platform / Nextflow Tower Bioinformatics workflow automation Docker and container technologies High-performance computing environments S3, IAM, EC2, VPC, Lambda Terraform or CloudFormation Cloud monitoring and logging tools Data Technologies Data Lake and Lakehouse architectures ETL/ELT frameworks Data modeling Data cataloging and governance API integrations Data quality frameworks DevOps & Automation GitHub/GitLab Jenkins, GitHub Actions, or similar tools #J-18808-Ljbffr