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 #J-18808-Ljbffr Planet Pharma Group