[Candidate must live in the Cincinnati or Chicago area as this position requires 1 day per week in the office.]

As a Lead Data Engineer, you will have the opportunity to build solutions that ingest, store and distribute our big data to be consumed by data scientists and our products. Our data engineers use Hadoop, PySpark, Airflow, Python, Hive, and other data engineering technologies and visualization tools, while working alongside our application developers to deliver data capabilities and services to our scientists, products, and tools.

Responsibilities

Take ownership of features and drive them to completion through all phases of the entire 84.51° SDLC.  This includes internal and external facing applications as well as process improvement activities:

• Lead the design of and develop Cloud and Hadoop based solutions
• Perform unit and integration testing
• Participate in implementation of BI visualizations
• Collaborate with architecture and lead engineers to ensure consistent development practices
• Provide mentoring to junior engineers
• Participate in retrospective reviews
• Participate in the estimation process for new work and releases
• Collaborate with other engineers to solve and bring new perspectives to complex problems
• Drive improvements in people, practices, and procedures
• Embrace new technologies and an ever-changing environment

Requirements:

• 5+ years proven ability of professional data development experience
• 3+ years experience with PySpark/Spark (This is a critical and mandatory requirement) 
• 3+ years proven ability of developing with Hadoop/HDFS
• 3+ years developing experience with either Java or Python
• 3+ years experience with Airflow
• Full understanding of ETL concepts
• Exposure to VCS (Git, SVN)
• Strong understanding of Agile Principles (Scrum)
• Bachelor’s degree typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another STEM degree.

 Preferred Skills – Experience in the following

• Exposure to NoSQL (Mongo, Cassandra)
• Exposure to Service Oriented Architecture
• Exposure to cloud platforms (Azure/GCP/AWS)
• Exposure to BI tooling e.g Tableau, PowerBI, Cognos
• Proficient with relational data modeling and/or data mesh principles
• Continuous Integration/Continuous Delivery

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