Senior Data Science Platform Engineer, (Senior Consultant, Data & Analytics)

Fearless is a digital integration consultancy on a mission to build a better tomorrow. They are seeking a Senior Data Science Platform Engineer to design and maintain scalable AWS environments for advanced analytics and machine learning, while collaborating with business stakeholders and supporting data science teams.

Responsibilities:

• Collaborate with business stakeholders to translate analytical and research requirements into scalable technical solutions
• Maintain Amazon SageMaker environments supporting machine learning workflows and model development
• Support JupyterLab, RStudio, Plotly Dash Enterprise, and Quarto platforms for data science teams
• Engineer scalable shared storage using Amazon FSx and S3 to enable cross-team data access
• Develop AWS cross-account data pipelines to securely move and transform data across organizational boundaries
• Build CI/CD automation to streamline platform deployments and reduce manual overhead
• Optimize cloud costs and monitor usage anomalies to ensure responsible stewardship of federal resources
• Produce SOPs, architecture documentation, and operational runbooks to support platform sustainability and knowledge transfer
• Support AI-enabled analytics platforms by maintaining infrastructure that enables data scientists and analysts to develop, test, and deploy machine learning and artificial intelligence solutions
• Develop test automation frameworks and scripts to validate infrastructure deployments, data pipelines, and system configurations
• Support operations and maintenance (O&M) activities, including user assistance, incident response, system monitoring, and routine platform maintenance
• Ensure compliance with organizational security standards and cloud governance policies by implementing security controls, conducting audits, maintaining access controls, and protecting sensitive data

Requirements:

• Minimum of 10 years of experience designing enterprise data architectures, with at least 5 years focused on cloud-native data platforms
• 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
• Experience as an AWS Solutions Architect designing and implementing production systems
• Proven experience with AWS Glue, SageMaker, FSx, and S3 in production data workflows
• Proficiency in Python, R, and SQL for data pipeline development and analytics support
• Experience working in Linux environments and managing infrastructure as code
• Experience with GitHub for version control and collaborative development
• Experience operating in a DevSecOps environment with automated security controls and compliance monitoring
• Experience extracting and transforming data within AI and ML platforms for research and analytics
• Experience with Agile Scrum methodologies supporting iterative platform delivery
• Experience supporting Treasury, IRS, CFPB, FDIC, OCC, Federal Reserve, or similar regulatory agencies
• AWS Machine Learning Specialty or AWS Data Engineer Associate certification
• Experience working with multiple stakeholders to mentor technical teams and drive collaborative outcomes