Job details

Lead Data Engineer (P3796)

84.51° Overview:

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°!

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As a Lead Data Engineer, you will have the opportunity to build solutions that ingest, transform, store, and distribute our big data to be consumed by data scientists and our products.

Our data engineers use PySpark/Python, Databricks, Hadoop, 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 data pipeline solutions 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:

Ability to design and plan complex processes and systems.
Solve problems with high ambiguity.
Focus on overall solution architecture.
Focus on continuous system improvements: simplification, performance, reliability, quality assurance.
Ability to implement an effective automated testing strategy.
Design impactful data pipeline monitoring.
Successfully launch projects of significant impact.
Initiate collaboration with other teams and programs.
Drive best practices via code and design reviews.
Coach, mentor, and provide technical assessments.
Work with Product to create a product roadmap.
Balance technology with business value

Requirements

5+ years proven ability of professional Data Development experience.
4+ years proven ability of developing with Databricks or Hadoop/HDFS.
4+ years of experience with PySpark/Spark.
4+ years of experience with SQL
4+ years of experience developing with either Python, Java, or Scala
Mastery of data modeling concepts
Full understanding of ETL concepts and Data Warehousing concepts
Experience with CI/CD pipelines
Experience with version control software
Strong understanding of Agile Principles (Scrum)
Bachelor's Degree (Computer Science, Management Information Systems, Mathematics, Business Analytics, or STEM)

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