84.51 Degrees

Data analytics for retail marketing decisions

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-time

About the Job

Requirements

A bachelor's degree in Computer Science, Management Information Systems, Mathematics, Business Analytics, or a STEM field is required.
At least 3 years of professional data development experience is required.
At least 3 years of experience developing with Databricks is required.
At least 3 years of experience with PySpark or Spark is required.
At least 3 years of experience developing with Python or Java is required.
A full understanding of ETL and data warehousing concepts is required.
Experience with pipeline orchestration is required.
Experience with continuous integration and continuous delivery is required.
Experience with version control software is required.
A strong understanding of Agile principles, including Scrum, is required.
Experience preparing and validating data for downstream consumers, with an emphasis on data quality, governance, and clear metadata documentation, is required.

Responsibilities

Take ownership of features and drive them to completion through all phases of the 84.51° software development lifecycle, including internal- and external-facing applications and 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 estimating new work and releases.
Collaborate with other engineers to solve complex problems and bring new perspectives.
Drive improvements in data engineering practices, procedures, and ways of working.
Prepare, validate, and organize governed data and metadata to support reliable analytics and downstream data consumers.

Desired Qualifications

Experience with Azure.
Experience with Databricks Delta Tables, Delta Lake, and Delta Live Tables.
Proficiency with relational data modeling.
Experience with Python library development.
Experience with Structured Streaming using Spark or other technologies.
Experience with Kafka or Azure Event Hub.
Experience with GitHub SaaS or GitHub Actions.
Exposure to business intelligence tools such as Tableau, Power BI, or Cognos.
Experience with Kubernetes and Azure Kubernetes Service (AKS).
Experience building application programming interfaces with FastAPI.

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.

QUALIFICATIONS, SKILLS, AND EXPERIENCE

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.

BONUS POINTS FOR EXPERIENCE IN THE FOLLOWING

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.

#LI-AB1

Pay Transparency and Benefits

The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.
Below is a list of some of the benefits we offer our associates:

Health: Medical: with competitive plan designs and support for self-care, wellness and mental health. Dental: with in-network and out-of-network benefit. Vision: with in-network and out-of-network benefit.
Wealth: 401(k) with Roth option and matching contribution. Health Savings Account with matching contribution (requires participation in qualifying medical plan). AD&D and supplemental insurance options to help ensure additional protection for you.
Happiness: Paid time off with flexibility to meet your life needs, including 5 weeks of vacation time, 7 health and wellness days, 3 floating holidays, as well as 6 company-paid holidays per year. Paid leave for maternity, paternity and family care instances.

Base Pay Range

$121,000—$169,000 USD

Base Pay Range 121000 - 169000 USD

About the Company

84.51 Degrees

Data analytics for retail marketing decisions

84.51 Degrees analyzes large volumes of consumer data to help retailers and consumer goods companies understand shopper behavior and tailor marketing strategies. Its main product is data analytics and predictive analytics tools that uncover consumer insights, trends, and preferences across generations. These insights are delivered to B2B clients via subscriptions, project-based work, or performance-based pricing, enabling clients to make data-driven decisions and optimize customer engagement across the purchasing journey. The company differentiates itself through a strong emphasis on culture and inclusive workplace values, which it views as important for driving collaboration and innovation. Overall, the goal is to help clients stay relevant and competitive by translating data into actionable marketing and merchandising strategies.

Company size: 1,001-5,000
Company stage: M&A
Total funding: $5.5M
Headquarters: Cincinnati, OH
Founded: 2015

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