Senior Director, Data Engineer

Senior Director Data Engineer

As a Senior Director Data Engineer at Capital One you will lead high-performing engineering teams working to define the future of data platforms and banking in the cloud. You will partner closely with product managers data scientists architects and executive leaders to deliver scalable data-driven solutions. Our Senior Directors are technical people leaders who drive data engineering strategy guide complex architectural decisions and translate business goals into impactful data platforms.

Senior Directors are expected to lead through technical vision operational rigor and strategic alignment. You will serve as a key owner for your domains technical health delivery velocity and system resilience. While shaping long-term data strategy and platform roadmaps you will inspire a culture of continuous learning innovation and high-impact delivery across your organization.

At Capital One we are creating responsible and reliable AI systems changing banking for good. For years Capital One has been an industry leader in using machine learning to create real-time personalized customer experiences and to protect those customers with world-class security. Our investments in technology infrastructure and world-class talent position us to be at the forefront of enterprises leveraging AI including in the defense of the enterprise itself.

The Identity Analytics & Intelligence organization sits at that intersection. We build the data foundations ML systems and security products that decide - in real time - who and what can access Capital Ones systems and that detect and respond when something looks wrong. As identity moves from a human problem to a machine and agentic one this organization is defining how a Fortune 100 bank secures workloads non-human identities and AI agents at scale.

We are looking for a senior technology executive to lead this organization: someone who sets multi-year platform strategy and owns the architecture who can partner with the CISO and C-suite in the morning and pressure-test a model design or a streaming pipeline in the afternoon.

• Own the enterprise strategy and multi-year roadmap for identity analytics access decisioning and AI/ML security platforms aligning AI/ML investment with 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 across Data Engineering ML Generative AI and Security Products including managers and senior individual contributors. Hire develop and retain top technical talent; set engineering standards and a high bar for well-managed delivery.
• Set technical direction hands-on. Review architectures model designs and system trade-offs. Stay close enough to the code and the data to make good calls under uncertainty and to earn credibility with the engineers you lead.
• Architect low-latency event-driven systems for real-time identity decisioning and threat detection based on streaming telemetry behavioral signals and contextual graph data.
• Design build and maintain robust ML infrastructure and pipelines supporting end-to-end workflows: 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 practices through 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 combining behavioral analytics ML-based intent determination and context graphs to secure AI agents and workload identities.
• Apply state-of-the-art LLM and GenAI techniques in production for threat-intelligence summarization automated incident triage and adaptive access-policy recommendation and introduce optimization techniques that improve scalability cost latency and throughput of large-scale production AI systems.
• Operate an automated governance function with pipelines from enterprise and IGA platforms operationalizing NIST controls with continuous control validation and audit-ready evidence.
• Lead enterprise readiness for emerging cyber risk posed by frontier AI models and agentic attack patterns.

Basic Qualifications:

• Bachelors 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 at least one of the following languages: 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

Preferred Qualifications:

• Masters Degree in Computer Science or a related field
• 12 years of experience in application development with demonstrated proficiency in Python SQL Scala or Java
• 8 years of hands-on experience designing deploying and operating data workloads in at least one public cloud environment (AWS Microsoft Azure or Google Cloud)
• 8 years of experience building or supporting distributed data or compute workloads using tools such as EMR Spark Glue or Databricks
• 8 years of experience designing implementing and operating real-time or streaming data pipelines
• 6 years of experience working on data observability (e.g. Monte Carlo Splunk) or data orchestration tools (e.g. Airflow Dagster)
• 8 years of experience working with unstructured or semistructured data using NoSQL databases (e.g. MongoDB Cassandra DynamoDB)
• 8 years of experience designing and supporting data warehousing solutions (e.g. Snowflake Redshift)
• 6 years of experience working in an Agile development environment
• 6 years of experience developing user-centric reusable data products
• 5 years of experience in Data Governance Data Governance Platforms Data Standardization and Data Modeling

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean VA: $314800 - $359300 for Sr. Director Data Engineer

New York NY: $343400 - $392000 for Sr. Director Data Engineer

Plano TX: $286200 - $326700 for Sr. Director Data Engineer

Richmond VA: $286200 - $326700 for Sr. Director Data Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidates offer letter.

This role is also eligible to earn performance based incentive compensation which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive competitive and inclusive set of health financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status exempt or non-exempt status and management level.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please. Capital One is an equal opportunity employer (EOE including disability/vet) committed to non-discrimination in compliance with applicable federal state and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries including to the extent applicable Article 23-A of the New York Correction Law; San Francisco California Police Code Article 49 Sections 4901-4920; New York Citys Fair Chance Act; Philadelphias Fair Criminal Records Screening Act; and other applicable federal state and local laws and regulations regarding criminal background inquiries.

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Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).