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°!
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Lead Data Engineer
Location: Cincinnati, OH / Chicago, IL
Summary
We are seeking a Lead Data Engineer to build modern data platform solutions that turn data into actionable insights, reporting and AI-enabled capabilities used to personalize the customer experience.
As a Lead Data Engineer, you will partner cultivate strategies and solutions to ingest, store, transform, and distribute data at scale. Our engineers use Snowflake, Databricks, Azure Data Factory (ADF), SQL, Python, JSON, and related technologies in agile scrum teams to develop products, tools, and features that support analytics, reporting, and AI-enabled capabilities.
Responsibilities
Take ownership of features and drive them to completion through all phases of the SDLC. This includes platform capabilities, data products, and process improvement activities such as:
- Lead design of data platform and SQL-based solutions
- Perform development of data pipelines, transformations, and orchestration workflows
- Design and implement solutions using Snowflake, Databricks, Azure Data Factory (ADF), SQL, Python, and JSON
- Support data ingestion, storage, transformation, and distribution
- Contribute to data platform architecture supporting analytical and operational use cases
- Execute unit, integration, and data validation testing
- Collaborate with team members to ensure consistent development practices
- Partner with analytics and data science teams to support AI/ML and advanced analytics use cases
- Help establish governed, scalable data foundations for AI-enabled capabilities
- Contribute to standards for data quality, governance, lineage, and observability
- Provide mentoring to junior resources
- Participate in retrospective reviews
- Participate in estimation for new work and releases
- Bring new perspectives to problems and be driven to improve yourself and the way things are done
Qualifications, Skills, and Experience
- Bachelor’s degree typically in Computer Science, Management Information Systems, Mathematics, Business Analytics, Engineering, or another technically strong program
- 5+ years proven ability of professional data engineering or data development experience
- Strong understanding of Agile Principles (Scrum)
- 5+ years proven ability developing with SQL
- Full understanding of ETL/ELT concepts and data warehousing concepts
- 3+ years developing experience with Python, Scala, or Java
- Hands-on experience with Snowflake, Databricks, and Azure Data Factory (ADF)
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Preferred Skills
- Azure data services
- Data platform architecture
- Event-driven or near real-time data patterns
- AI/ML-enabled data solutions
- Generative AI or LLM-enabled workflows
- Data governance, metadata, and lineage tooling
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