Senior Data Engineer (P3957)

Key Skills

Agile methodologies, Apache Cassandra, Apache Hadoop, Azure, Continuous Integration & Continuous Delivery - CI/CD, Data Warehousing, Databricks, ETL frameworks, Git, HDFS, Java Programming, NoSQL, Oracle, PowerBI, PySpark, Python Programming, Scala Programming, Spark Core, SQL, SQL Server, Tableau

Job Description

84.51° is a retail data science, insights and media company. We help the Kroger company, consumer packaged goods companies, agencies, publishers and affiliated partners create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting edge science, we leverage 1st party retail data from nearly 1 of 2 US households and 2BN+ transactions to fuel a more customer-centric journey utilizing 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

As a Senior 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 Python, Hadoop, PySpark, Hive, and other data engineering technologies and visualization tools 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:

• Participate in design and development of Hadoop and Cloud-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 proven ability of developing with Hadoop/HDFS and SQL (Oracle, SQL Server)
• 3+ years of experience with PySpark/Spark
• 3+ years of experience developing with either Python, Java, or Scala 
• Full understanding of ETL concepts and Data Warehousing concepts
• Exposure to VCS (Git, SVN)
• Strong understanding of Agile Principles (Scrum)
• Bachelor’s Degree (Computer Science, Management Information Systems, Mathematics, Business Analytics, or STEM)

 Preferred Skills – Experience in the following

• Experience with Azure 
• Exposure to NoSQL (Mongo, Cassandra)
• Experience with Databricks
• Exposure to Service Oriented Architecture
• Exposure to BI Tooling (Tableau, Power BI, Cognos, etc.) 
• Proficient with Relational Data Modeling and/or Data Mesh principles
• Experience with CI/CD - Continuous Integration/Continuous Delivery