Senior Data Engineer (P1754) (P1752)

84.51° Overview

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

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us at 84.51°!

Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with the Kroger Family of Companies (i.e. H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant status)

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 the design and development of Databricks and Cloud-based solutions
- Implement automated unit and integration testing
- Collaborate with architecture and lead engineers to ensure consistent development practices
- Provide mentoring to junior engineers

· Collaborate within a cross-functional team of data scientists, Product partners, and engineers to translate analytical needs into reliable data pipelines and scalable solutions

- 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 data engineering practices, procedures, and ways of working
- Embrace new technologies and an ever-changing environment
- Prepare, validate, and organize governed data and metadata to support reliable analytics and downstream data consumers.

Requirements

Bachelor’s Degree (Computer Science, Management Information Systems, Mathematics, Business Analytics, or STEM); 3+ years proven ability of professional Data Development experience; 3+ years proven ability of developing with Databricks; 3+ years of experience with PySpark/Spark; 3+ years of experience developing with either Python or Java; Full understanding of ETL concepts and Data Warehousing concepts; Experience with Pipeline Orchestration; Experience with CI/CD; Experience with version control software; Strong understanding of Agile Principles (Scrum); Experience preparing and validating data for downstream consumers, with an emphasis on data quality, governance, and clear metadata documentation.

Nice to have

Experience with Azure; Experience with Databricks Delta Tables, Delta Lake, Delta Live Tables; Proficient with Relational Data Modeling; Experience with Python Library Development; Experience with Structured Streaming (Spark or otherwise); Experience with Kafka and/or Azure Event Hub; Experience with Github SaaS / Github Actions; Exposure to BI Tooling (Tableau, Power BI, Cognos, etc.); Experience with Kubernetes and Azure Kubernetes Service (AKS).; Experience building APIs with FastAPI.