Lead Data Engineer (Python, PySpark, AWS)
$197,300–$225,100 year
On-siteRichmond, Virginia, United States or McLean, Virginia, United States
Job Summary
Collaborate with Agile teams to design, develop, test, implement, and support full-stack technical solutions using Java, Scala, Python, and open-source RDBMS and NoSQL databases. Work with developers specializing in machine learning and distributed microservices to deliver robust cloud-based solutions on AWS, Redshift, and Snowflake that drive experiences for millions of Americans. Perform unit tests and conduct code reviews to ensure rigor, elegance, and performance tuning. Participate in internal and external technology communities, experiment with emerging tools, and mentor engineering members. Deliver powerful experiences supporting financial empowerment while driving major transformation initiatives within the company.
Required Qualifications
- Bachelor's Degree
- At least 4 years of experience in application development
- At least 2 years of experience in big data technologies
- At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)
Desired 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
- Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion
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