Cloud Data Engineer - PySpark

Responsibilities: for the Data Cloud Engineer Include: Design and maintain scalable ETL/ELT data pipelines using Azure Synapse, Databricks, AWS Glue, and related cloud technologies. Develop large-scale data transformations using PySpark, Spark SQL, Python, and SQL . Build data ingestion frameworks for structured and unstructured data, including relational databases, CSV, JSON, and REST APIs. Implement full and incremental data loads, Change Data Capture (CDC) , and rerunnable pipeline architectures. Design and support cloud-based data lakes, data warehouses, and analytics-ready datasets . Implement data quality and governance controls including schema validation, RBAC, lineage, cataloging, and credential management. Monitor and troubleshoot data pipelines for performance, failures, latency, logging, and operational reliability. Implement CI/CD pipelines supporting automated deployments and environment promotion. Partner with cloud and cybersecurity teams to maintain compliance with RMF, STIG, FedRAMP, and DoD security requirements . Support cloud data migration, integration, and modernization initiatives across Azure and AWS environments. Qualifications: for the Data Cloud Engineer Include: 10+ years of experience designing and supporting production-grade cloud data pipelines . Strong experience with Azure Synapse, Databricks, Azure Data Factory, and/or AWS data services . Advanced experience with PySpark, Spark SQL, Python, and SQL . Experience with ETL/ELT, CDC, data lakes/warehouses, data quality, and governance . Experience implementing CI/CD and automated deployments for cloud data environments. Bachelor's degree in a related technical field. Active Secret clearance required. Compensation: for the Data Cloud Engineer Includes: Salary Range: $110,000 - $140,000 depending on experience. Comprehensive Benefits: Medical, Dental, Vision, 401(k), PTO, and Paid Holidays.