Metas Solutions

Senior Data Engineer

Metas Solutions Atlanta, Georgia, United States

Business Consulting and Services · 51-200 employees

19 h ago
data-engineer Senior (5-10 yrs) Full-time United States
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About the role

The Senior Data Engineer will design, implement, and maintain enterprise-grade ETL/ELT pipelines while managing complex data models and lakehouse environments. They will collaborate with cross-functional teams to ensure the scalability, security, and performance of critical data systems that support organizational decision-making.

What they look for

Python SQL ETL/ELT Pipelines Data Architecture Databricks Azure Data Factory Data Modeling Cloud Engineering Data Governance Metadata Management CI/CD NoSQL Data Security API Integration Infrastructure Optimization

Requirements

Candidates must have at least 8 years of experience in data engineering, software engineering, or database architecture, including proficiency in Python and SQL. A bachelor's degree in a quantitative field and U.S. citizenship or permanent residency are required.

Full description

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. See www.metassolutions.com for further details about us and careers with Metas.

Job Description:

Metas Solutions has an "immediate opening" for a talented Senior Data Engineer residing in the Atlanta, Georgia or D.C. Metro Area who will manage a critical role within the organization, who can help manage and transform complex data ecosystems to provide scalable, analysis-ready solutions that inform senior leadership decisions.

The ideal candidate 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 collaborate closely with a team of data scientists, operational leaders, and infrastructure architects to ensure the integrity, scalability, reliability, and performance of the organization's critical data systems. You will play an integral role in supporting data-driven operations and ensuring that systems remain efficient, secure, and capable of meeting evolving business and technical requirements.

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

Qualifications:

  • 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
  • Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder)

Additional 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, government policies, and compliance frameworks
  • Certifications such as Azure Data Engineer Associate Experience

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