Senior Data Engineer; Senior Consultant, Engineering & Technical Services

Senior Data Engineer

At Fearless, we are seeking a Senior Data Engineer as part of our Senior Consultant, Engineering and Technical Services career path to design and build cloud-native data engineering pipelines supporting semantic processing, knowledge graph construction, and AI-enabled analytics for federal financial regulatory systems. This role supports a large-scale data modernization initiative that processes structured and unstructured regulatory filings, financial disclosures, and enterprise datasets to enable semantic search, natural language query, and GraphRAG capabilities across federal data assets.

This role operates in a hybrid work environment and requires on-site presence at the customer location in Washington, DC approximately 2–3 days per week to support collaboration with federal stakeholders, with the remaining time performed remotely.

• Design and develop enterprise data pipelines supporting structured data ingestion, unstructured document ingestion, metadata extraction, semantic enrichment, entity resolution, and knowledge graph population.
• Build and maintain AWS-native ETL/ELT solutions.
• Develop data pipelines supporting XBRL processing, financial disclosures, regulatory filings, and enterprise datasets.
• Implement semantic processing architectures using Databricks, Spark, Delta Lake, Open Search, and Neptune.
• Develop graph generation pipelines that produce nodes, edges, relationships, and ontological mappings.
• Build metadata extraction and lineage tracking capabilities.
• Support GraphRAG and semantic search implementations.
• Implement APIs supporting natural language query (NLQ) and semantic retrieval services.
• Develop CI/CD pipelines and Infrastructure-as-Code deployments.
• Build automated testing frameworks and data quality monitoring capabilities.
• Implement security controls that support federal compliance requirements.
• Optimize pipeline performance, scalability, and cloud costs.
• Support Agile delivery and sprint-based development.

Fearless Impact:

• Fosters collaboration with cross functional teams by taking the initiative and driving conversations
• Coach, mentor, and develop peers that elevate team capability and technical expertise using clear and persuasive communication of engineering solutions to both technical and non-technical audiences
• Earn the trust of your customer and teammates by delivering world class services.
• Drive accountability and delivery by ensuring project objectives are not only met on time but aligned with client priorities and Fearless standards of excellence. Anticipate risks and implement proactive solutions to keep initiatives on track.
• Take ownership of risk management by monitoring deliverables across the team, identifying issues early, and coaching teammates on mitigation strategies while keeping leadership informed.
• Shape client engagement and intelligence-gathering efforts by actively cultivating relationships with stakeholders, synthesizing insights across the client organization and partner ecosystem, and providing Fearless leaders with actionable recommendations that inform strategy and strengthen delivery outcomes.

Fearless Customer Impact:

• Deliver expected outcomes relative to high quality code and maintainable systems
• Offer and implement innovative solutions that include engineering best practices through new tools, frameworks and methodologies
• Lead and align stakeholders with product and project goals that advance customer satisfaction as well as Fearless' objectives, strategy, and mission
• Serve as a trusted advisor in your area of expertise

Project Skill and Experience Requirements:

• Minimum of 7 years of data engineering experience
• Experience building cloud-native data pipelines.
• Proven experience building data pipelines using Python, SQL, Spark, Databricks, and AWS services.
• Demonstrated experience implementing data lakes, lakehouse architectures, and ETL/ELT frameworks with metadata management, data lineage, and data quality controls.
• Experience with graph databases such as Neptune, Open Search, and vector databases supporting semantic search and AI/ML workflows.
• Familiarity with XBRL-formatted data, financial reporting datasets, or regulatory filings in federal or financial services contexts.
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field
• Ability to obtain and maintain Public Trust clearance.

Preferred

Skills and Experience:

• Experience implementing GraphRAG solutions and natural language query architectures using Databricks Genie and NLQ architectures.
• Experience building knowledge graphs exceeding hundreds of millions of nodes and relationships using AWS Neptune and Open Search.
• Experience supporting federal AI modernization initiatives.
• AWS Data Analytics Specialty certification or Databricks Data Engineer Professional certification.

• Analytical Thinking:
  The ability to observe and interpret information, break down…