Lead Data Engineer (Python, Spark)

impact beyond the scope of their project/team by building relationships and advocating for best practices

• Use technical expertise to guide engineers to ensure data pipelines, data models and code are efficient and reliable

• Design and develop scalable data architectures and systems that extract, store, and process large amounts of data

• Develop and architect scalable data pipelines and ETL processes using programming languages such as Python, Java, Scala, and frameworks like Spark and Flink

• Collaborate with Data Scientists, Machine Learning Engineers, Business Analysts and/or Product Owners to understand their requirements and provide efficient solutions for data exploration, analysis, and modeling

• Build highly available and scalable data solutions in an ambiguous environment while sharing design patterns with teams

• Automate integrations and data pipelines using data governance and various testing techniques

• Use cutting edge technologies to develop modern data pipelines supporting Machine Learning and Artificial Intelligence

Team Info: 

The Finance Data Refinery Recon team in the Enterprise Data and Machine Learning (EDML) organization supports the AWS-hosted Data Processing application that provides automated reconciliations of mission-critical datasets for the Finance Tech organization. You will get opportunities and exposure to evolving data pipeline patterns, and dive deep into the unique engineering challenges these bring around data integrity, security, timeliness, and maintainability. You’ll focus on designing and implementing data pipeline architecture to ensure high availability of our managed environment. You will have an opportunity to work on the application layer written in Python/Scala running on EC2s orchestrated by AROW, debug application and environment issues , and help optimize and continuously improve pipeline patterns.

Basic Qualifications: 

• Bachelor’s Degree 

• At least 6 years of experience in application development (Internship experience does not apply)

• At least 2 years of experience in big data technologies 

• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications:

• 7+ years of experience in application development including Python, SQL, Scala, or Java

• 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)

• 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)

• 4+ year experience working on real-time data and streaming applications 

• 4+ years of experience with NoSQL implementation (Mongo, Cassandra) 

• 4+ years of data warehousing experience (Redshift or Snowflake) 

• 4+ years of experience with UNIX/Linux including basic commands and shell scripting

• 2+ years of experience with Agile engineering practices 

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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