Job ID: VA-762942 (96790506)
Remote/Local Azure Data Engineer/Architect (15+/DP-203) with ETL/ELT, Data Factory/Lake, JSON, Parquet, Synapse, Python, PySpark, PII, Devops, CI/CD and Agile/Scrum experience
Location: Richmond, VA (ELECT)
Duration: 6 Months
Position: 1(2)
Skills:
• At least 3 years of experience building and maintaining ETL/ELT pipelines in enterprise environments using Azure-native tools. Required 3 Years
• Hands-on expertise with Azure Data Factory, Dataflows, Synapse Pipelines, or similar orchestration tools. Required 3 Years
• Proficiency in SQL, Python, or PySpark for transformation logic and data cleansing workflows. Required 3 Years
• Experience with Delta Lake, Azure Data Lake Storage Gen2, JSON, and Parquet formats. Required 3 Years
• Ability to build modular, reusable pipeline components using metadata-driven approaches and robust error handling. Required 3 Years
• Familiarity with public data sources, government transparency datasets, and publishing workflows. Required 3 Years
• Knowledge of data masking, PII handling, and encryption techniques to manage sensitive data responsibly. Required 3 Years
• Experience with data quality frameworks, including automated validation, logging, and data reconciliation methods. Required 3 Years
• Strong grasp of DevOps/DataOps practices, including versioning, testing, and CI/CD for data pipelines. Required 3 Years
• Experience supporting data publishing for oversight, regulatory, or open data initiatives is highly desirable. Required 3 Years
• Certifications such as DP-203 (Azure Data Engineer Associate) or Azure Solutions Architect are a plus. Highly desired 3 Years
Description:
This position will support the design and delivery of secure, scalable, and traceable data pipelines in Azure, with a focus on integrating and transforming sensitive, public-facing datasets. The candidate will build ingestion workflows and transformation logic to support reporting, analytics, and public transparency initiatives. This role requires experience with Azure-native tools, strong ETL/ELT capabilities, and a strong commitment to data quality, auditability, and responsible data use. The candidate will be working with an existing software development team in an Agile/Scrum environment.