Senior Data Engineer

About the role

Metas Solutions excels in providing strategic consulting, program management, and data-driven analytics to federal public health agencies. Our expertise enhances health systems and delivers measurable outcomes, helping agencies achieve their mission. We collaborate with federal partners to implement agile solutions for national public health initiatives, driving impactful changes through cutting-edge programs that strengthen communities and promote well-being.

Responsibilities

• 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

Requirements

• 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
• Bachelor's degree in computer science, Engineering, Information Systems, or a related, quantitative field

Qualifications

• 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
• Previous CDC Experience
• Certifications such as Azure Data Engineer Associate