Data Cloud Engineer

Design, develop, and maintain scalable cloud-based ETL/ELT pipelines using Azure and AWS technologies. Build and optimize large-scale data transformations using PySpark and Spark SQL. Develop data ingestion frameworks supporting structured and unstructured data, including databases, APIs, JSON, and flat files. Implement full and incremental data loading strategies, including Change Data Capture (CDC). Design and support enterprise data lakes, data warehouses, and analytics environments. Implement data quality, governance, and security controls including schema validation and RBAC. Monitor, troubleshoot, and optimize production data pipelines. Support CI/CD implementation and automated deployments. Partner with cloud engineering, cybersecurity, DevOps, and software development teams.

Active Secret Clearance. Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related field. 8+ years of data engineering experience. Strong hands-on experience with PySpark, Spark SQL, Python, and SQL. Experience with Azure Synapse Analytics, Databricks, and/or AWS data services. Experience building and supporting production-grade ETL/ELT pipelines. Experience with data ingestion, integration, transformation, and CDC. Experience troubleshooting production data environments and implementing monitoring and logging., Experience with Azure Data Factory, AWS Glue, Redshift, Amazon S3, and Oracle. Experience supporting federal or DoD cloud modernization programs. Familiarity with RMF, STIG, and FedRAMP. Experience working in Agile development environments.

Salary: $120,000 - $140,000 depending on experience