Data Engineer

Description:

What You Will Do

Perform complex queries using SQL and / or other tools (e.g., R, Python Pandas, PySpark)
Manage ETL (Extract, Transform, Load) functions
Develop, build, test, and maintain scalable data pipeline architectures and tools
Partner with data scientists/analysts and cross-functional teams to discover, collect, cleanse, and refine the data needed for analysis and modeling
Operate in a cloud environment and assess environment specifications and requirements for big data
Work with data integration and management tools such as databases (cloud and on-prem; relational and NoSQL), Databricks and a variety of tools from major cloud providers (AWS, Azure, GCP)
Understand client needs and translate to technical requirements and Jira cards for implementation

What You Will Need

U.S. citizenship and Secret Clearance.
B.S./B.A. is required plus 3+ years of relevant professional experience
Experience developing data pipelines / ETLs and performing data engineering using Spark and Databricks
Experience performing data engineering to enable data science and machine learning
Experience in Python or Scala
Understanding relational databases, columnar data warehouses, NoSQL, and other storage types
Proficiency in SQL
Ability to instrument basic automation and CI/CD
Familiarity with cloud-based services (AWS, Azure, GCP)
Knowledge/experience designing and building distributed systems for scalability and security
Understanding of Agile development methodologies