Job Description
Supply Chain Data Strategy and Cloud Operation are core to the Co and it operations.
With sales of over $100 B, the capability of delivering critical data and building cloud first solutions our teams offer are one of the most critical capabilities of the company.
Were looking for individuals who can bring their core set of knowledge as well as learn new tools to provide new data and capabilities to support 's ever growing Supply Chain.
Accountable for developing and delivering technological responses to targeted business outcomes.
Analyze, design and develop enterprise data and information architecture deliverables, focusing on data as an asset for Supply Chain and the overall enterprise.
Understand and follow reusable standards, design patterns, guidelines, and configurations to deliver valuable data and information across the enterprise, including direct collaboration with 84.51, where needed.
Demonstrate the companys core values of respect, honesty, integrity, diversity, inclusion and safety.
Key Responsibilities
Create and leverage Databricks notebooks to source, shape and store data using SQL, Python, PySpark
Utilize enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses
Ensure there is clarity between ongoing projects, escalating when necessary, including direct collaboration with 84.51
Define high-level migration plans to address the gaps between the current and future state
Analyze technology environments to detect critical deficiencies and recommend solutions for improvement
Promote the reuse of data assets, including the management of the data catalog for reference
Top skills needed:
Azure Data Lake (Gen 2)
Azure Databricks
SQL
Unity Catalog
Alation
Power BI
Terraform
GitHub Actions
Interviews: First round with HM 30 min, second round panel with Tech lead, PM and another Engineer
HM will be reviewing candidates end of this week (4/22)
Target start date: ASAP
Project agile scrum practices, joining a warehouse data engineering team warehouse data domain, Implementing Manhattan which is a 2-5 year project, Data mapping to set up data domain
Hiring process - HM review prescreenings, share candidates with Tech Lead, Interview top 5ish candidates