Data Engineer 5 - Enterprise Risk Management

Data Engineer 5 - Enterprise Risk ManagementDo 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 Engineers who are passionate about marrying data with emerging technologies. In this role, you'll be at the forefront of driving a major transformation across Capital One.What You'll Do:Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologiesInfluence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systemsUtilize programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and SnowflakeShare 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 communityCollaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowermentIndependently design, build and deliver world-class cloud data solutions and applications with little or no support from supervisors or managersArchitect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelinesServe 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 understandingDesign and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, ensuring robust performance under increasing data volume and business demandsServe as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineersLead 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 requirementsBasic Qualifications: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 4 years of experience in distributed dataAt least 4 years of experience with SQLAt least 4 years of experience programming with at least one of the following languages: Python, Java, or ScalaAt least 4 years of experience designing and developing data pipelinesAt least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systemsPreferred Qualifications:Master's Degree in Computer Science or a related field8+ years of experience in data engineering4+ years of data modeling experience9+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java5+ 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 Databricks5+ years of experience designing, implementing, and operating real-time or streaming data pipelines3+ 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 environment3+ years of experience developing user-centric reusable data productsCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.McLean, VA: $229,900 - $262,400 for Data Engineer 5Richmond, VA: $209,000 - $238,500 for Data Engineer 5Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.