Description
As a Senior Staff Data Engineer at Capital One, you will be part of a community of technical experts working to define the future of data platforms and banking in the cloud.
You will work alongside our talented team of data engineers, data scientists, machine learning experts, product managers and people leaders. Our Senior Staff Data Engineers are leading experts in their domains, helping devise practical, scalable and reusable data solutions to complex problems.
You will drive innovation at multiple levels, helping optimise business outcomes while delivering strong data and technology solutions.
At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organisational boundaries.
You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed.
You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community.
Senior Staff Data Engineers are expected to lead through technical contribution.
You will operate as a trusted advisor for our key data technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organisation.
You will specialise in a particular subject area, but your input and impact will be sought and expected throughout the organisation.
About the Team:
You will join the Pipelines and External Data team within Enterprise Data, serving as a Senior Director-level Individual Contributor (IC).
This role demands a visionary and hands-on leader to drive the technical strategy for data pipelines and sharing capabilities leveraged by all lines of business inclusive of both internal and external data availability.
Your focus is on driving innovation, best practices, engineering / delivery acceleration, platform scalability, operational excellence, performance, resiliency, and being a beacon for other ICs.
We require deep expertise in AWS infrastructure, Lakehouse architecture, Kafka, Flink, Spark, Snowflake, and Databricks to mature these enterprise-scale systems and execute technical strategy.
You will be both visionary, influential, and hands-on writing Python, SQL, Java, and/or Scala code.
What You’ll Do:
- Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
- Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team
- Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
- Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organisation
- Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in a unified manner
- Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent
- Drive the strategic direction of the data engineering practice by continuously researching and assessing emerging trends in data, AI, and engineering, and developing a roadmap to integrate relevant innovations into the overall data platform
- Lead strategic alignment and integration decisions across multiple data systems and business units, championing a unified data architecture that supports seamless, scalable, and governed data flow across the organisation
- Own the creation, management, and socialisation of data strategy artifacts, ensuring comprehensive documentation is available to inform and guide enterprise-level decisions and initiatives (e.g., data governance policies, architecture blueprints, data product roadmaps)
- Serve as a technical "force-multiplier," independently owning the end-to-end design and coding of critical data projects while influencing architectural standards and mentoring junior engineers to scale the team's capabilities and output
Basic Qualifications:
- 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 5 years of experience in data architecture
- At least 3 years of experience building applications in AWS
- At least 7 years of experience programming with at least one of the following languages: Python, Java, or Scala
- At least 6 years of experience designing and developing data pipelines
- At least 4 years of experience in data modelling and designing end-to-end data solutions using both relational and non-relational database systems
Preferred Qualifications:
- Master’s Degree in Computer Science or a related field
- 11+ years of experience in data engineering
- 8+ years of data modelling experience
- 3+ years of experience with ontology standards for defining a domain
- 2+ years of experience deploying machine learning models
- 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 with unstructured/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
Salary Information:
The minimum and maximum full-time annual salaries for this role are listed below, by location.
Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff Data Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff Data Engineer New York, NY: $343,400 - $392,000 for Sr. Staff Data Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff Data Engineer
Benefits:
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.