This role pays more than
82%
of similar roles. Most pay
$140,000–$216,000
— the shaded band above.
At the midpoint, this role pays about
$224k
versus about
$178k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
936 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 933 roles with salary data.
As a Senior Manager Data Engineer (Databricks, Pyspark, Snowflake), you will lead high-performing Agile teams in designing, developing, and supporting scalable data engineering solutions across full-stack and cloud platforms. You will manage a diverse team of engineers while overseeing the design and health of data platforms and pipelines to ensure quality and operational efficiency. Your daily responsibilities include reviewing architecture designs, data models, and pipeline code, as well as mentoring talent and driving technical strategy for large-scale transformations. The role requires proficiency in Python, Spark, Databricks, Snowflake, SQL, Java, or Scala, along with experience in lakehouse architecture, distributed microservices, and real-time streaming pipelines. You will solve complex business problems by building robust cloud-first data solutions and establishing common design patterns to ensure code maintainability across various data platforms and infrastructure.
Lead Agile teams in designing, developing, and supporting scalable data engineering solutions across cloud platforms.
Perform hands-on technical reviews of architecture designs, data models, and pipeline code in Python, Spark, Databricks, and Snowflake.
Architect and enforce common data engineering design patterns to ensure code quality and reusability.
Oversee the health of data platforms and pipelines while establishing standards for scalability and data quality.
Lead and mentor a diverse team of engineers to improve talent density and foster career development.
Execute large-scale, transformative data initiatives by making critical architectural decisions and evaluating platform choices.
Communicate complex technical concepts and data outcomes clearly to internal and external stakeholders.
What we're looking for
Bachelor's Degree or higher in Computer Science or a related quantitative field.
At least 6 years of experience in application development.
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 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 solutions using relational and non-relational databases.
Master's Degree in Computer Science or a related field (preferred); 9+ years of application development; 5+ years in cloud, distributed workloads, streaming pipelines, or warehousing (preferred).