Description
We are seeking experienced Data Engineers to join our team, who are passionate about marrying data with emerging technologies. As a Capital One Data Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within Capital One.
Responsibilities:
- Lead design and build Enterprise Level scalable, low-latency, fault-tolerant streaming data platform that provides meaningful and timely insights
- Build the next generation Distributed Streaming Data Pipelines and Analytics Data Stores using streaming frameworks (Flink, Spark Streaming) using programming languages like Java, Scala, Python
- Lead a group of engineers building data pipelines using big data technologies (Spark, Flink, Kafka, Snowflake, AWS Big Data Services, Snowflake, Redshift) on medium to large scale datasets
- Influence best practices for Data Pipeline design, Data architecture and processing of structured and unstructured data
- Work in a creative & collaborative environment driven by agile methodologies with focus on CI/CD, Application Resiliency Standards, and partnership with Cyber & Security teams
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
- Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
- Work with a team of developers with deep experience in machine learning, distributed microservices, and full stack systems
- Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
- Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 4 years of experience in application development
- At least 2 years of experience in distributed data
- At least 2 years of experience with SQL
- At least 2 years of experience with one programming language (Python, Java, or Scala)
- At least 2 years of experience in data pipeline design and development
- At least 1 year of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems
Preferred Qualifications:
- 7+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
- 4+ years of hands-on experience designing, deploying and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
- 4+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
- 4+ years of experience designing, implementing, and operating real-time or streaming data pipelines
- 2+ years of experience working on data observability or data orchestration tools
- 4+ years of experience working with unstructured or semi-structured data using NoSQL databases
- 4+ years of experience designing and supporting data warehousing solutions
- 2+ years of experience working in an Agile development environment
- 2+ years of experience developing user-centric reusable data products
Benefits:
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being