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Lead Data Engineer (P3330)

Cincinnati, OH

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.

Join us at 84.51°!

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LEAD DATA ENGINEER – P3330

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.

Join us at 84.51°!

__________________________________________________________

As Lead Data Engineer, your role will involve collaboration with cross-functional teams, leveraging cutting-edge technologies, and ensuring scalable, efficient, and secure data engineering practices.  You’ll be working with data across 2 cloud platforms (Azure and GCP) and thus will be working with a wide variety of technologies.  A strong emphasis will be placed on expertise in GCP, Vertex AI, and advanced feature engineering techniques.

Responsibilities
Take ownership of systems, processes, and the tech stack while driving features to completion through all phases of the entire 84.51° SDLC.  This includes internal and external facing applications as well as process improvement activities:

  • Provide Technical Leadership: Offer technical leadership to ensure clarity between ongoing projects and facilitate collaboration across teams to solve complex data engineering challenges.
  • Build and Maintain Data Pipelines: Design, build, and maintain scalable, efficient, and reliable data pipelines to support data ingestion, transformation, and integration across diverse sources and destinations, using tools such as Kafka, Databricks, and similar toolsets.
  • Drive Digital Innovation: Leverage innovative technologies and approaches to modernize and extend core data assets, including SQL-based, NoSQL-based, cloud-based, and real-time streaming data platforms.
  • Implement Feature Engineering: Develop and manage feature engineering pipelines for machine learning workflows, utilizing tools like Vertex AI, BigQuery ML, and custom Python libraries.
  • Implement Automated Testing: Design and implement automated unit, integration, and performance testing frameworks to ensure data quality, reliability, and compliance with organizational standards.
  •  Optimize Data Workflows: Optimize data workflows for performance, cost efficiency, and scalability across large datasets and complex environments.
  • Mentor Team Members: Mentor team members in data principles, patterns, processes, and practices to promote best practices and improve team capabilities.
  • Draft and Review Documentation: Draft and review architectural diagrams, interface specifications, and other design documents to ensure clear communication of data solutions and technical requirements.
  •  Cost/Benefit Analysis: Present opportunities with cost/benefit analysis to leadership, guiding sound architectural decisions for scalable and efficient data solutions.

Requirements:
Bachelor’s degree typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another STEM degree.

  • Proven experience in leading cross-functional teams and managing complex projects from inception to completion
  • 5+ years of professional Data Development experience.
  • 5+ years of experience with SQL and NoSQL technologies.
  • 3+ years of experience building and maintaining data pipelines and workflows.
  • 2+ years of experience developing with Python.
  • 3+ years of experience developing Kafka solutions.
  • 2+ years of experience in feature engineering for machine learning pipelines.
  • Experience with GCP services such as BigQuery, Vertex AI Platform, Cloud Storage, AutoMLOps, and Dataflow.
  • Experience with CI/CD pipelines and processes.
  • Experience with automated unit, integration, and performance testing.
  • Experience with version control software such as Git.
  • Full understanding of ETL and Data Warehousing concepts.
  • Strong understanding of Agile principles (Scrum).

Preferred Qualifications

  • Knowledge of Structured Streaming (Spark, Kafka, EventHub, or similar technologies).
  • Experience with GitHub SaaS/GitHub Actions.
  • Experience understanding Databricks concepts.
  • Experience with PySpark and Spark development.
  • Experience with Service Oriented Architecture.

IMPORTANT INFO

Candidates must be able to come into the office on Monday, Tuesday, Wednesday and Thursday of each week.

#LI-SSS

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: Hybrid work environment. 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.

 

Pay Range

$91,000 - $218,750 USD

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Location options vary by role and are stated in each job posting. Our Headquarters are in Cincinnati, OH. We also have hubs in Chicago, Deerfield, New York and Portland. Not all roles are open in all locations. 

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California Applicant Privacy Notice can be found here:
https://www.8451.com/privacy-policy-84-51-application-privacy-note

Questions 

Individuals who have questions about this Applicant Notice should contact 84.51° by using the Contact Us link at the bottom of our homepage at www.8451.com.

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84.51° Demographic Questions

Together, we are stronger and can achieve more

At 84.51°, we believe a diverse and inclusive work environment is essential to the work we do as a data science company. Just as no two Kroger customers are alike, no two 84.51° associates are alike. We understand the importance of fostering an inclusive culture: to encourage our associates to bring their authentic selves to work – embracing who they are and celebrating what they can become.

We continually strive to ensure 84.51° is a place where all people feel like they belong, are respected and valued regardless of who they are, where they are from and what experiences they’ve had. By meeting our 3-year D&I roadmap goals and commitments, we will continue our journey towards becoming a destination for diverse, driven, and authentic minds.

Your responses will be used (in aggregate only) to help us identify areas of improvement in our process.

Your responses will not be associated with your specific application and will not in any way be used in the hiring decision.

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