Cloud Data Developer/Engineer

• Experience 7-10+ years in Data Engineering/Cloud Development. • 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. Pay ranges between 75-85/hr based on experience