Senior Cloud Data Engineer, (Senior Consultant, Data & Analytics)

Fearless is a digital integration consultancy on a mission to build a better tomorrow. They are seeking a Senior Cloud Data Engineer to design and develop enterprise-scale data pipelines and cloud-native solutions for federal financial regulatory systems, enabling analytics and AI-driven decision-making.

Responsibilities:

• 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 using Python, Spark, and Databricks to process regulatory filings and financial datasets
• Implement semantic processing architectures using Delta Lake, OpenSearch, and Neptune to support advanced analytics and AI/ML workflows
• Develop graph generation pipelines that produce nodes, edges, relationships, and ontological mappings at enterprise scale
• Build metadata extraction and lineage tracking capabilities to ensure data provenance and auditability across the platform
• Implement APIs supporting natural language query (NLQ) and semantic retrieval services for end-user consumption
• Develop CI/CD pipelines and Infrastructure-as-Code deployments with automated testing, data quality monitoring, and deployment validation
• Implement security controls that support federal compliance requirements and organizational security standards
• Optimize pipeline performance, scalability, and cloud costs to improve operational efficiency
• Support Agile delivery by participating in sprint planning, backlog refinement, development, testing, and continuous integration activities

Requirements:

• Minimum of 7 years of data engineering experience building cloud-native data pipelines and distributed processing systems
• Experience working at or in support of the U.S. Securities and Exchange Commission (SEC), with knowledge of SEC business processes, systems, and regulatory mission
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent work experience
• Ability to obtain and maintain Public Trust clearance
• Proven experience building data pipelines using Python, SQL, Spark, Databricks, and AWS services in production environments
• Demonstrated experience implementing data lakes, lakehouse architectures, and ETL/ELT frameworks with metadata management and data lineage capabilities
• Experience with graph databases such as Neptune, OpenSearch, 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
• Experience implementing GraphRAG solutions and natural language query architectures using Databricks Genie and NLQ frameworks
• Experience building knowledge graphs exceeding hundreds of millions of nodes and relationships using AWS Neptune and OpenSearch
• Experience supporting federal AI modernization initiatives and regulatory compliance requirements
• AWS Solutions Architect Professional, Certified Kubernetes Administrator, or AWS Security Specialty certifications