Technical Compliance Analyst - USDS

Responsibilities

About the Team

The Data Governance Engineering team is at the heart of our data strategy. Our mission is to ensure the integrity, security, and compliance of our data assets through robust lifecycle management, automated compliance frameworks, and advanced content assurance standards.

Unlike traditional compliance roles, we sit at the intersection of Engineering, Policy, and Risk. We don't just follow rules; we build the technical guardrails and automated systems that allow the company to innovate safely at scale.

About the Role

As a Technical Compliance Analyst, you will not be handling repetitive first-line tickets (which are managed by our outsourced partners). Instead, you will act as the critical technical bridge between R&D and the Policy/Risk Control teams and support in managing the critical "data filters" (Gateways) that synchronize information between production environments and external parties.

You will dive deep into data lineage, review complex technical requests (including code and SQL), and make high-stakes compliance decisions in a fast-paced environment. You will also leverage and optimize AI Agents to automate governance workflows and conduct A/B testing on compliance logic. This role is not just about processing tickets or managing SLAs; it is about high-stakes technical auditing, process engineering, and leveraging automation to secure one of the world’s most complex data ecosystems.

• Technical Bridge & Mediation:
  Serve as the primary technical consultant between Engineering teams and Policy/Risk stakeholders to translate complex legal/compliance requirements into actionable technical specifications.
• Advanced Technical Review:
  Perform high-level audits of data access, microservices, and API integrations. You must be able to read and understand code/SQL to identify potential compliance risks that automated scanners might miss.
• Data Lineage & Scenario Analysis:
  Rapidly map and understand complex data lineage (data flows) across various business scenarios to ensure end-to-end data integrity and regulatory adherence.
• Compliance Decision Making:
  Make authoritative "Approve/Reject" decisions on complex technical requests within strict SLA windows, balancing business velocity with rigorous risk control. Demonstrated ability to manage competing priorities and maintain quality.
• AI-Driven Governance:
  Utilize and tune AI Agents to enhance governance efficiency. This includes Context Engineering, prompt optimization, and conducting A/B testing on automated compliance models.
• Risk & Data Analysis:
  Conduct deep-dive data analysis to identify systemic risks, trends, and bottlenecks in the data lifecycle, providing data-backed recommendations to senior leadership.
• Framework Evolution:
  Partner with the engineering team to build and refine automated compliance frameworks, moving away from manual checks toward "Compliance-as-Code." Develop new and continuously improve existing operational documentation (runbooks, review criteria, escalation paths).

Minimum Qualifications:

• Technical Literacy:
  Ability to read and interpret code (e.g., Python, Java, or Go) and SQL. You should be comfortable discussing system architecture with developers.
• Analytical Mindset:
  Proven experience in technical risk analysis or data analysis. You can look at a data flow and pinpoint where the "leak" or "risk" is.
• AI Savvy:
  Hands-on experience or strong theoretical knowledge of AI/LLM tools. Familiarity with Context Engineering and the ability to use AI to automate workflow-related tasks.
• Decision Making:
  Experience working in a fast-paced environment where you must make accurate compliance decisions under tight SLAs. High attention to detail, sound judgment, and able to make decisions for approvals or rejections within defined policy boundaries; ability to escalat[e] appropriately when criteria is unclear.
• Strategic Communication and Stakeholder Management:
  Exceptional ability to explain technical risks to non-technical policy makers and explain policy constraints to engineers. Serve as one of the primary cross-functional partners for ticket review operations and data field governance, coordinating with Product, Global Risk and Compliance, and other Engineering teams.

• Bachelor’s or Master’s degree in Computer Science or a related technical field.
• Data Governance Expertise:
  Strong understanding of data lifecycle management, data lineage, and privacy frameworks (e.g., GDPR, CCPA).
• Experience in Data…