Position contingent on contract award - details below are subject to change based on final award.

You will be at the technical forefront of data pipeline development, data architecture, and infrastructure optimization, ensuring that the organization’s analytical operations rest on a robust and secure foundation. This is a role for a highly technical and driven individual capable of building enterprise-level data management systems that support current and future data science initiatives. Your expertise will enable critical insights, informing strategies, optimizing data processes, and facilitating efficient decision-making. You will work alongside a team of data scientists, operational leaders, and infrastructure architects to maintain the integrity, scalability, and performance of critical data systems within the organization.  

• Design, implement, and maintain enterprise‑grade ETL/ELT pipelines using Python and SQL
• Build, optimize, and manage data models, warehouses, and lakehouse environments (e.g., Databricks)
• Develop processes for ingesting, cleaning, validating, and transforming large‑scale datasets from APIs, relational sources, and unstructured systems
• Implement data quality, metadata management, and governance controls to ensure consistency and trust in analytics workflows
• Collaborate with cloud engineering teams to deploy and manage data solutions on Azure
• Monitor, troubleshoot, and improve pipeline performance using logging, alerting, and CI/CD practices
• Document data architecture, pipeline logic, and operational procedures to enable team collaboration and maintainability

• 8+ years of experience in data engineering, software engineering, or database architecture
• 6+ years of experience in Python and SQL with experience building scalable ETL/ELT pipelines
• 2+ years of experience with cloud data ecosystems like Azure Data Factory
• 1+ years of experience with modern data processing frameworks like Databricks
• Experience with integrating and transforming data from diverse formats and systems (APIs, flat files, relational sources)
• Knowledge of relational and NoSQL databases, data modeling, and schema design
• Knowledge of data governance, security, and compliance principles for enterprise data environments
• Ability to support on-site work in Atlanta, GA or Washington, DC
• Bachelor’s degree in computer science, Engineering, Information Systems, or a related, quantitative field

Nice If You Have:

• Experience with supporting key data engineering efforts in a government related environment
• Experience with collaborating with data scientists and analysts to define data models that meet evolving organizational goals
• Knowledge of IT infrastructure practices and data access methodologies
• Knowledge of advanced data security practices, governance policies, and compliance frameworks
• Certifications such as Azure Data Engineer Associate