Senior Data Engineer
P707
Confirmed live in the last 24 hours
84.51 Degrees

1,001-5,000 employees

Retail data science company enhancing customer experiences
Company Overview
84.51° stands out as a leading retail data science company, utilizing advanced data science and predictive analytics to create personalized experiences for shoppers, thereby providing a competitive edge to its clients. The company's unique strength lies in its access to first-party retail data from nearly half of US households and over 2 billion transactions, which enables a more customer-centric approach. With its specialized services like 84.51° Insights, 84.51° Loyalty Marketing, and Kroger Precision Marketing, 84.51° helps brands effectively engage customers at every point of their purchasing journey.
Data & Analytics
Consumer Goods

Company Stage

N/A

Total Funding

$5.5M

Founded

2015

Headquarters

Cincinnati, Ohio

Growth & Insights
Headcount

6 month growth

0%

1 year growth

9%

2 year growth

24%
Locations
Chicago, IL, USA • Highland Park, IL, USA • Cincinnati, OH, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Agile
Python
Apache Spark
SQL
Java
Hadoop
Business Analytics
CategoriesNew
Data Engineering
Data Management
Data & Analytics
Requirements
  • 4+ years proven ability of professional Data Development experience
  • 3+ years proven ability of developing with Databricks or Hadoop/HDFS
  • 3+ years of experience with PySpark/Spark
  • 3+ years of experience with SQL
  • 3+ years of experience developing with either Python, Java, or Scala
  • Full understanding of ETL concepts and Data Warehousing concepts
  • Experience with CI/CD
  • Experience with version control software
  • Strong understanding of Agile Principles (Scrum)
  • Bachelor's Degree (Computer Science, Management Information Systems, Mathematics, Business Analytics, or STEM)
Responsibilities
  • Take ownership of features and drive them to completion through all phases of the entire 84.51° SDLC
  • 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
  • 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