[Hiring] Senior Staff Data Engineer @Capital One

Role 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 optimize 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 organizational 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 organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.

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.

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 modeling and designing end-to-end data solutions using both relational and non-relational database systems

Requirements

• Master’s Degree in Computer Science or a related field (Preferred)
• 11+ years of experience in data engineering (Preferred)
• 8+ years of data modeling experience (Preferred)
• 3+ years of experience with ontology standards for defining a domain (Preferred)
• 2+ years of experience deploying machine learning models (Preferred)
• 12+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java (Preferred)
• 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) (Preferred)
• 8+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks (Preferred)
• 8+ years of experience designing, implementing, and operating real-time or streaming data pipelines (Preferred)
• 6+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster) (Preferred)
• 8+ years of experience with unstructured/semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) (Preferred)
• 8+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift) (Preferred)
• 6+ years of experience working in an Agile development environment (Preferred)
• 6+ years of experience developing user-centric reusable data products (Preferred)

Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being.
• Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).