Cloud Data Developer Engineer

Experience:

• Experience 7-10+ years in Data Engineering/Cloud Development.

Core Requirements & Technical Skills:

• Proven experience designing and building scalable data pipelines (ingestion, transformation, validation) using AWS, Python, and Databricks (Spark/PySpark).
• Experience working with structured, semi-structured, and unstructured data. Exposure to life sciences data formats such as DICOM, FASTQ/BAM/PLINK, or SAS7BDAT is strongly preferred.
• Hands-on experience with modern data platforms such as Databricks.
• Experience with data governance tools (e.g., Immuta) is preferred.
• Familiarity with analytics and statistical tools such as Tableau, R/Posit, or SAS is a plus.
• Deep expertise in AWS data services (e.g., S3, Lambda, RDS, FSx/EFS) and cloud-native architecture best practices.
• Strong programming skills in Python and SQL, with experience in PySpark; working knowledge of R is a plus.
• Experience with CI/CD and orchestration tools such as GitHub, Azure DevOps, and Apache Airflow.
• Working knowledge of data science and machine learning concepts (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with Databricks, including cluster usage and performance optimization; exposure to Unity Catalog and platform administration is a plus.
• AWS and/or Databricks certifications are preferred.
• Experience with Kubernetes/EKS is a plus.
• Experience architecting technology solutions to meet business requirements.
• Experience managing technology projects end to end through planning, design, build, testing and deployment phases.
• Understanding of Computer System Validation for GxP vs Non-GxP technologies is preferred.
• Strong communication skills and ability to work collaboratively with internal IT partners, business partners and external vendors.