> Markdown version of [/jobs/ext/2013890-cyber-ai-data-engineer-senior-consultant](https://www.wearedevelopers.com/jobs/ext/2013890-cyber-ai-data-engineer-senior-consultant). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cyber AI Data Engineer Senior Consultant - **Company:** Deloitte T.T.L. - **Location:** Baltimore, MD, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Audit Trail, Cyber Security, Information Engineering, Data Governance, Data Systems, Python (Programming Language), Meta-Data Management, Operational Databases, Cloud Services, Standard Sql, Runbook, Software Engineering, Workflow Management Systems, Enterprise Software Applications, Data Classification, Data Management, Cyber Warfare, Stream Processing, Data Pipelines - **Published:** August 10, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/cyber-ai-data-engineer-senior-consultant-baltimore-md-usa-58885331 ## About the Role and capabilities for governance, risk, and cyber operations (evidence summarization, control testing assist, Q&A, copilots) * Engineer integrations between data platforms, GRC workflows, and enterprise systems with observability and runbooks * Collaborate with Cyber, Risk, Compliance, Privacy, and Legal to translate requirements into implementable controls and guardrails Tasks * Bachelor's degree or equivalent practical experience * 4+ years of data engineering and software development using Python and SQL * Experience building production data pipelines and data models for batch/stream processing and cloud deployments * Experience implementing data governance controls including data classification, encryption, audit logging, and lineage/metadata management * Experience supporting governance, risk, and compliance workflows and large language model-enabled applications * Ability to travel 0-25% Key requirements * ## Description Experteer Overview In this role, you will design and operate governed data foundations to support cyber risk and AI-enabled security workflows. You'll build scalable data pipelines and models for risk reporting, controls monitoring, and audit-ready evidence. You will work with cross-functional partners to translate GRC requirements into robust data solutions and governance patterns. The role combines modern data engineering with governance and compliance in regulated environments, offering impact at scale. You will contribute to innovative AI-enabled capabilities that accelerate governance and security operations. Compensation / Benefits * Build scalable batch and stream data pipelines ingesting security telemetry and compliance artifacts into governed stores * Design data models for risk, controls, and audit evidence to enable self-service analytics and dashboards * Implement data quality, lineage, metadata, and access controls for auditability and defensible evidence * Develop AI-enabled capabilities for governance, risk, and cyber operations (evidence summarization, control testing assist, Q&A, copilots) * Engineer integrations between data platforms, GRC workflows, and enterprise systems with observability and runbooks * Collaborate with Cyber, Risk, Compliance, Privacy, and Legal to translate requirements into implementable controls and guardrails Tasks * Bachelor's degree or equivalent practical experience * 4+ years of data engineering and software development using Python and SQL * Experience building production data pipelines and data models for batch/stream processing and cloud deployments * Experience implementing data governance controls including data classification, encryption, audit logging, and lineage/metadata management * Experience supporting governance, risk, and compliance workflows and large language model-enabled applications * Ability to travel 0-25% Key requirements * ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Resilient by Design: Building Robust Architectures in High-Stakes Financial Systems](https://www.wearedevelopers.com/videos/2106-resilient-by-design-building-robust-architectures-in-high-stakes-financial-systems) - [Technical Documentation - How Can I Write Them Better and Why Should I Care?](https://www.wearedevelopers.com/videos/681-technical-documentation-how-can-i-write-them-better-and-why-should-i-care) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Analytics in the Age of Agentic AI: A tour of ClickHouse and Langfuse](https://www.wearedevelopers.com/videos/100240-analytics-in-the-age-of-agentic-ai-a-tour-of-clickhouse-and-langfuse) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)