This Senior Data Engineer role supports the CDC/DMAC program by designing, building, and optimizing enterprise data solutions for mission-critical federal operations. The position is hybrid, primarily onsite one day per week, based in the Atlanta, GA or Washington, DC Metro area.

Role Summary

In this position, you will develop and maintain scalable data engineering solutions that enable trusted enterprise analytics. Work includes ETL/ELT pipeline development, lakehouse and warehouse implementation with Databricks, and cloud-based data solution delivery within Microsoft Azure.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL.
Build and optimize data models, data warehouses, and lakehouse environments using Databricks.
Ingest, clean, validate, and transform large-scale datasets from APIs, relational databases, flat files, and unstructured sources.
Implement data quality, metadata management, and governance controls to support trusted analytics.
Develop and manage cloud-based data solutions on Microsoft Azure, including Azure Data Factory.
Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and reliability.
Support automated deployment and operational processes using logging, alerting, and CI/CD practices.
Collaborate with data scientists, analysts, engineers, and business stakeholders to translate data requirements into scalable technical solutions.
Document data architecture, pipeline logic, data models, and operational procedures.

Required Qualifications

8+ years of experience in data engineering, software engineering, database architecture, or a related technical field.
6+ years hands-on experience with Python and SQL, including building scalable ETL/ELT pipelines.
2+ years experience working with Azure data services, including Azure Data Factory.
1+ years hands-on experience with Databricks or similar modern data processing platforms.
Experience integrating and transforming data from APIs, flat files, relational databases, and other sources.
Strong understanding of relational and NoSQL databases, data modeling, and schema design.
Knowledge of data quality, governance, security, and compliance practices.
Experience troubleshooting and optimizing data pipelines.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
Ability to support on-site work in Atlanta, GA or the Washington, DC Metro area.
Must be a U.S. Citizen or Lawful Permanent Resident.
Public Trust eligibility required.

Technologies

Python
SQL
Databricks
Microsoft Azure
Azure Data Factory
CI/CD

Preferred Qualifications

Prior CDC or federal government experience supporting health data initiatives.
Experience working with data scientists and analysts on data models supporting analytics and machine learning.
Knowledge of enterprise infrastructure and data access methods.
Experience with advanced data security, governance, and compliance frameworks.
Microsoft Azure or related data engineering certification.

Location and Clearance

Location: Hybrid (primarily in Atlanta, GA or Washington, DC / Maryland / Virginia area), 1 day per week onsite.
Clearance/Suitability: Public Trust eligibility required.

Compensation

Salary range: USD 150,000 - 165,000 per year. Final compensation is based on technical skills, experience, education, certifications, and clearance.

Benefits

Medical, Dental, and Vision coverage through national providers
401(k) with company match (eligible after 6 months; vesting applies)
Company-paid Life and AD&D insurance with additional voluntary options
Short-term disability (company-paid) and long-term disability options
Employee Assistance Program (EAP) with 24/7 confidential support and mental health resources
Telehealth and virtual care options available through medical plans
Pet insurance, legal services, and identity theft protection options
Paid Time Off (PTO) for eligible employees
Paid federal holidays for salaried employees
Access to wellness programs, discounts, and lifestyle benefits

Senior Data Engineer

Job Description