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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cyber AI Data Engineer Senior Consultant - **Company:** Deloitte T.T.L. - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Audit Trail, Information Engineering, Data Governance, Data Infrastructure, Data Stores, Python (Programming Language), Metadata, Meta-Data Management, Operational Databases, Standard Sql, Runbook, Software Engineering, Systems Integration, 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-atlanta-ga-usa-58885325 ## About the Role and * Develop AI-enabled capabilities to accelerate governance, risk, compliance and cyber operations (evidence summarization, Q&A, copilots, ticket triage, exception reasoning) * Engineer integrations between data platforms, governance workflows, and enterprise systems with observability and runbooks * Collaborate with Cyber, Risk, Compliance, Privacy, and Legal teams to translate requirements into implementable controls and guardrails Tasks * Bachelor's degree or equivalent practical experience * 4+ years in data engineering and software development using Python and SQL * Experience building production data pipelines and data models for batch/stream processing on cloud platforms * Experience implementing data governance controls including data classification, encryption, audit logging, lineage/metadata management Key requirements * ## Description Experteer Overview In this role you will design and operate production-grade data foundations that power cyber risk, compliance evidence, and AI-enabled security workflows. You'll build scalable data pipelines and governance-enabled data stores to support risk reporting, controls monitoring, and auditable evidence generation. You partner with Cyber, Risk, Compliance, Privacy, and Legal teams to translate requirements into guardrails, enabling secure, compliant operations at enterprise scale. This is a hands-on engineering role that blends data engineering with GRC expectations in regulated environments. Compensation / Benefits * Build scalable batch and stream data pipelines ingesting security telemetry, control evidence, and compliance artifacts into governed data stores * Design data models for risk, controls, and audit artifacts to enable self-service analytics and dashboards * Implement data quality, lineage, metadata, and access controls to support auditability and defensible evidence * Develop AI-enabled capabilities to accelerate governance, risk, compliance and cyber operations (evidence summarization, Q&A, copilots, ticket triage, exception reasoning) * Engineer integrations between data platforms, governance workflows, and enterprise systems with observability and runbooks * Collaborate with Cyber, Risk, Compliance, Privacy, and Legal teams to translate requirements into implementable controls and guardrails Tasks * Bachelor's degree or equivalent practical experience * 4+ years in data engineering and software development using Python and SQL * Experience building production data pipelines and data models for batch/stream processing on cloud platforms * Experience implementing data governance controls including data classification, encryption, audit logging, lineage/metadata management Key requirements * ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [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) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [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: The Deciding Factor in AI Success](https://www.wearedevelopers.com/videos/100310-data-the-deciding-factor-in-ai-success) - [No Keys for the Robot: GitOps as the Control Plane for Autonomous Agents](https://www.wearedevelopers.com/videos/100095-no-keys-for-the-robot-gitops-as-the-control-plane-for-autonomous-agents) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [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) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)