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Own the cost and AI-leverage layer of the analytics platform behind Capital One Shopping — the systems between petabyte-scale data and the humans and tools that query it. This is an own-and-build role, not a maintenance seat: you own the production platforms below, and in your first six months you ship three net-new systems on top of them. You'll report to the Engineering Director for the Shopping data platform as one of two senior IC pillars of the analytics org.

You own, support, and evolve three production platforms — ideation through implementation to production support — and you're the SME and mentor for the analysts, BAs, and engineers who use them:

• A data warehousing platform serving ~250K queries/day over ~20PB.
• An event ingestion pipeline taking in 6–7 billion events/day.
• The Airflow orchestration platform.

You own the technology choices and the strategic backlog and priorities for this surface — and you carry ongoing production support and an on-call rotation for these platforms and the models on them. You build the three net-new systems below on top of that operational base.

• A cost-attribution pipeline that parses Trino query logs at production traffic and attributes real AWS dollars to every report, query, user, and dbt model — reconciled against a $~750K/month cloud bill.
• A forecast-driven autoscaling control loop for the shared Trino cluster and dbt worker pool — turning today's event-only Nomad autoscaler (Prime Day, Cyber Week) into steady-state, forecast-driven capacity. The single largest lever on the analytics AWS bill.
• A production Gen AI system — natural-language-to-SQL or RAG over the data catalog — with real LLM tool-use, grounding, and cost guardrails, adopted by internal teams.

Kafka streaming backbone into an S3 lakehouse (Hive + Iceberg), Cassandra, Postgres, DynamoDB, ElasticSearch, Aurora MySQL. Queried through Trino/Presto and Spark SQL, modeled in dbt, orchestrated on Airflow and Nomad and containers (Docker/Kubernetes), on a deep AWS footprint. SQL and Python daily; Go, Java, and TypeScript/JavaScript across the surrounding platform.

"Manager" is the level, not the job — this is an individual-contributor role, and you'll spend most of your day hands-on in the editor. Roughly 70% building: writing the log-parsing and cost-attribution logic and its dbt models, building and tuning the forecast-driven autoscaler control loop, and building the RAG / natural-language-to-SQL system yourself. The other ~30% is technical coordination — reconciling your cost numbers with Finance, the R&D memo, aligning report owners — not status decks or people-management. Daily rhythm is multi-terminal Claude Code: query-log analysis in one, dbt work in another, AI iteration in a third. No direct reports — you build.

• 10+ years engineering experience owning and supporting mission-critical applications and platforms in production
• Deep experience with Kafka and streaming technologies and platforms
• Experience with enterprise data technologies and platforms
• A track record working with extremely large traffic and data volumes
• Fluency across a real stack: JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, open-source RDBMS and NoSQL databases, container orchestration (Docker and Kubernetes), and a broad range of AWS tools and services
• Forecast- or workload-driven infrastructure scaling on a shared platform — you've scaled shared infra up and down against a forecast, not just event-driven bursts
• Production Gen AI — RAG design, vector/graph stores, LLM tool-use — on top of a longer ML/AI arc (ranking, recommendation, or comparable production ML predating the 2023 Gen AI boom)
• 0-to-1 delivery of a product that booked measurable revenue or adoption in its first weeks, plus a lead-engineer role modernizing an ingest pipeline off a legacy provider onto a cloud-native stack
• Experience directing a cross-team migration or deprecation at senior-executive scope to completion
• A broad background and a genuinely fast learner — the stack keeps moving
• Comfortable working with large teams on large-scale systems, and cross-functionally (weekly Finance/BizOps and Analytics cadences)
• Claude Code fluency — daily use, skill authoring, PR-level deliverables (hard requirement)

• Bachelor's Degree
• At least 6 years of experience in software engineering (Internship experience does not apply)
• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

• Master's Degree
• 9+ years of experience in at least one of the following: JavaScript, Java, TypeScript, SQL, Python, or Go
• 4+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service
• 4+ years of experience in open source frameworks
• 1+ years of people management experience
• 2+ years of experience in Agile practices

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.

Remote (Regardless of Location): $209,000 - $238,500 for Sr. Lead Software Engineer

McLean, VA: $229,900 - $262,400 for Sr. Lead Software 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 candidate's 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 the Capital 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 City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

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).