Senior Manager Data Engineer (Databricks, Pyspark, Snowflake)

Capital One • Chicago, IL

1d • $209,000 - $238,500

About The Position

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Data Engineering leaders who are passionate about building high-performing teams, driving technical strategy and marrying data with emerging technologies. In this role, you’ll be at the forefront of mentoring engineering talent and leading major technology transformations across Capital One.

Requirements

• Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 6 years of experience in application development (Internship experience does not apply)
• At least 3 years of people management experience
• At least 2 years of experience driving technical delivery of roadmap features
• At least 4 years of experience programming with at least one of the following languages: Python, Java, or Scala
• At least 4 years of experience designing and developing data pipelines
• At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Nice To Haves

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

Responsibilities

• Lead high-performing Agile teams in designing, developing, testing, and supporting scalable data engineering solutions across full-stack and cloud platforms
• Influence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Maintain hands-on technical engagement by reviewing architecture designs, data models and pipeline code across Python, Spark, Databricks, and Snowflake environments
• Share your passion for staying on top of trends in data, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the data community
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
• Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelines
• Serve as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alignment and shared understanding
• Oversee the design and health of data platforms and pipelines, establishing standards for scalability, resilience, data quality and operational efficiency
• Lead, mentor, and grow a diverse team of data engineers, acting as a force-multiplier to elevate talent density, foster technical career development, and drive engineering best practices
• Lead and execute large-scale, transformative data initiatives from end to end, independently driving critical architectural decisions and evaluating platform choices, such as Snowflake versus Databricks, based on technical and business requirements

Benefits

• performance based incentive compensation
• cash bonus(es)
• long term incentives (LTI)
• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Senior