Senior Director, Data Engineer

Lead the engineering strategy behind cloud-based identity analytics and AI/ML security platforms for banking, with a role designed for impact across multi-year programs. This onsite position in McLean, VA offers performance-based incentive compensation and a comprehensive benefits package to support total well-being.

The Senior Director, Data Engineer will own the technical and architectural direction for identity analytics, access decisioning, and AI/ML security, guiding teams to deliver scalable, real-time data and machine learning systems. You will also drive enterprise readiness for emerging cyber risk from frontier AI models and agentic attack patterns.

• Own the enterprise strategy and multi-year roadmap for identity analytics, access decisioning, and AI/ML security platforms, aligning AI/ML investment to business, audit, and regulatory priorities and partnering with C-suite and CISO-org stakeholders to fund next-generation capabilities.
• Lead and grow a 50+ person organization spanning Data Engineering, ML, Generative AI, and Security Products, including managers and senior individual contributors, while hiring, developing, and retaining top technical talent and setting engineering standards for well-managed delivery.
• Set technical direction hands-on by reviewing architectures, model designs, and system trade-offs, staying close to code and data to make high-quality decisions under uncertainty.
• Architect low-latency, event-driven systems for real-time identity decisioning and threat detection using streaming telemetry, behavioral signals, and contextual graph data.
• Design, build, and maintain robust ML infrastructure and pipelines for end-to-end workflows including feature extraction, training, testing, guardrails, evaluation, deployment, and both real-time and batch inference with high performance, scalability, and reliability.
• Drive the evolution of MLOps with automated, metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring and observability for models in production.
• Build the intelligence layer for agentic and non-human identity using behavioral analytics, ML-based intent determination, and context graphs to support secure AI agents and workload identities.
• Apply state-of-the-art LLM and GenAI techniques for production threat-intelligence summarization, automated incident triage, and adaptive access-policy recommendation, including optimization to improve scalability, cost, latency, and throughput for large-scale AI systems.
• Operate an automated governance function with pipelines from enterprise and IGA platforms, operationalizing NIST controls through continuous control validation and audit-ready evidence.
• Lead enterprise readiness for emerging cyber risk posed by frontier AI models and agentic attack patterns.

• Bachelor’s Degree in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• At least 9 years of experience in data engineering.
• At least 7 years of people management experience.
• At least 7 years of experience programming with Python, Java, or Scala
  .
• At least 5 years of experience driving technical delivery of roadmap features.
• At least 6 years of experience designing and developing data pipelines.
• At least 4 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.

Python, Java, Scala, NIST, AWS, Microsoft Azure, Google Cloud, EMR, Spark, Glue, Databricks, Airflow, Dagster, Monte Carlo, Splunk, MongoDB, Cassandra, DynamoDB, Snowflake, Redshift, SQL

• Performance based incentive compensation
  , which may include cash bonus(es) and/or long…