Data Engineer III

Job Requirements

This senior-level Data Engineer will lead the design and development of scalable, secure, and automated data pipelines across our portfolio of federal digital services. The Data Engineer III will architect and implement cloud-native solutions that enable agencies to make better, faster, data-informed decisions. This role will collaborate closely with product owners, analysts, DevSecOps engineers, and federal data teams to build robust systems for ingesting, transforming, and delivering high-value datasets—aligned with federal mandates such as the Foundations for Evidence-Based Policymaking Act, Federal Data Strategy, and CIO Council Data Maturity Goals.

The Impact You Will Create:

This project supports the modernization of a large-scale federal disclosure and data management platform. The work involves designing, developing, and maintaining a secure, cloud-based system that improves how information is submitted, processed, and accessed by the public. The team will leverage Agile, DevSecOps, and user-centered design practices to deliver scalable, high-impact digital services that enhance transparency, compliance, and accessibility. Efforts include building modern APIs and web interfaces, implementing Zero Trust security, automating testing and deployments, and driving continuous improvement through cloud-native and AI-enabled solutions.

Your Responsibilities in This Role:

At Fearless, we seek candidates who blend technical know-how with sharp problem-solving and advisory skills to drive real impact in the communities we serve. Here are the key qualifications for this role.

• Design, develop, and maintain scalable ETL/ELT pipelines using tools like Apache Airflow, AWS Glue, Spark, Databricks, or custom Python solutions.
• Implement data workflows in cloud platforms, primarily AWS, using native services with IaC.
• Create and maintain logical, conceptual, and physical data models to support analytics, APIs, and operational workloads.
• Ensure data lineage, provenance, classification, and access controls follow NIST 800-53, OMB M-19-23, and agency-specific data policies.
• Implement automated data quality checks, validation logic, and reconciliation processes to ensure data integrity.
• Collaborate with analysts and scientists to support BI dashboards, AI/ML pipelines, and predictive analytics initiatives.
• Support data access through secure, well-documented RESTful APIs, GraphQL, and data catalogs.
• Participate in sprint ceremonies, backlog grooming, and estimation with cross-functional Agile teams.
• Develop documentation (runbooks, lineage diagrams, schema definitions) to support ATO, audit readiness, and internal knowledge sharing.

Work Experience

Skills and Qualifications We Require at Fearless:

At Fearless, we seek candidates who blend technical know-how with sharp problem-solving and advisory skills to drive real impact in the communities we serve. Here are the key qualifications for this role.

• Must possess or have the ability to obtain a Public Trust clearance
• Bachelor’s Degree required
• 7+ years of professional experience in data engineering or backend data systems Development.
• Strong fluency in SQL and Python for ETL workflows.
• Expertise with cloud data platforms.
• Experience with data pipeline orchestration.
• Solid understanding of data modeling, data warehousing, and performance tuning.
• Familiarity with DevOps/CI/CD tools and version-controlled data assets.
• Experience working with data cataloging and metadata tools.
• Demonstrated knowledge of federal data governance, privacy, and security controls (NIST 800-53, FISMA, FedRAMP).
• Strong communication skills and ability to work across teams (analysts, security, product owners).

Project Specific Qualifications:

This role includes additional qualifications to help us deliver bold, impactful work for our clients.

• Prior experience supporting federal data platforms.
• Experience with Apache Spark, Databricks, or AWS EMR for large-scale data processing.
• Familiarity with BI tools.
• Exposure to data lakehouse architecture and Delta Lake or Iceberg formats.
• Familiarity with semantic layer/ontology development for metadata-rich environments.
• Knowledge of AI/ML pipelines and integration with model-serving platforms (e.g., SageMaker, MLflow).

Physical Requirements:

• Ability to sit for extended periods while working on a computer or during meetings.
• Must be able to travel occasionally to client sites or company meetings.
• Ability to communicate effectively via phone, email, and in-person, requiring clear speech, listening, and written communication skills.
• Ability to move within an office environment, including reaching for files, using office equipment, and occasional light lifting (up to 10 pounds).
• The role will require working primarily on-site in Washington, D.C. for at least the first six months of the project.