Data Cloud Engineer

Zachary Piper Solutions is seeking a Data Cloud Engineer to support a long-term federal modernization program focused on enterprise cloud data solutions and mission-critical analytics within secure DoD environments. The role will modernize enterprise data infrastructure by developing secure, scalable data pipelines, cloud data platforms, governance controls, and operational processes for advanced analytics and reporting.

Responsibilities:

• Design, develop, and maintain production-grade ETL/ELT pipelines, with a strong emphasis on hands-on, high-performance PySpark development and Spark SQL optimization
• Build and maintain scalable data pipelines using Azure Synapse Analytics, Databricks, AWS Glue, and related cloud technologies
• Develop ingestion frameworks for structured and unstructured data, including relational databases, flat files, JSON, nested data, and REST APIs
• Implement full and incremental data loads, including CDC, late-arriving records, and rerunnable pipeline architectures
• Design and maintain cloud data lakes, warehouses, and analytics-ready datasets supporting enterprise reporting and operational decision-making
• Implement data quality and governance controls, including schema validation/enforcement, schema drift, RBAC, lineage, cataloging, and credential management
• Monitor and troubleshoot pipelines for performance, latency, failures, logging, alerting, and operational reliability
• Support CI/CD, automated deployments, rollback strategies, and environment promotions across cloud data environments
• Collaborate with cybersecurity, cloud, DevOps, and software engineering teams to support RMF, STIG, FedRAMP, and DoD security requirements, data migrations, integrations, and Agile delivery

Requirements:

• 10+ years of recent experience designing and operating scalable, production-grade data pipelines using Azure Synapse and/or Databricks, w/ a Bachelors degree in Computer Science, Data Science, Engineering, Information Systems, or a related field
• Strong hands-on PySpark development experience is required, including demonstrated high-performance coding skills developing ETL pipelines; candidates without this experience will not be considered
• Advanced experience with Spark SQL, Python, and SQL, including large-scale data transformation and optimization
• Experience ingesting structured and unstructured data and implementing full/incremental loads, CDC, and rerunnable pipeline architectures
• Strong experience with data quality, schema validation/enforcement, pipeline monitoring, logging, alerting, and troubleshooting
• Experience implementing CI/CD practices and automated deployments for data pipelines and cloud environments
• Experience with data governance, RBAC, and credential management in secure cloud environments
• Hands-on experience with Azure and/or AWS data services, including Azure Synapse, Azure Data Factory, Databricks, AWS Glue, Redshift, and S3
• Active Secret clearance