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

Fearless•Baltimore, MD

22h•$120,588 - $195,955•Remote

About The Position

At Fearless, we are seeking a Senior Cloud Data Engineer as part of our Senior Consultant, Data and Analytics career path to design and build cloud-native data engineering pipelines that lead to the enablement of analytics, business intelligence, statistical analysis, and AI-driven decision support 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 that will be used to modernize data platforms using AWS cloud services. The Senior Consultant is an expert in data analysis, engineering, and science. This role will possess the necessary skills at an advanced level of proficiency to drive organizational transformation by architecting scalable data platforms, building advanced machine learning solutions, and mentoring customers and teams to become data-driven organizations. The role involves working with executives, project teams, and internal leaders across departments to identify opportunities where data can accelerate missions, create efficiencies, and deliver technical excellence.

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.

Nice To Haves

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.

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.