Engineer, Data

As a Data Engineer on the Supply Chain team, you will build and automate the data pipelines that turn raw operational data — vendor receiving, warehouse movement, transportation, and inventory — into trusted, per-distribution-center metrics. You will be empowered to develop data solutions that give business teams faster, data-driven visibility into how the supply chain is performing, engaging with app owners, technology teams, analysts, and business partners to understand capability requirements and build data solutions based on priorities. Job Description

Experience Required: 3+ years. 3+ years of relevant technical experience working with various data engineering methodologies such as data integration and data pipelines (ETL/ELT) to activate against data at scale. 3+ years of experience with data modeling for analytic project activities that include design, curation, and management of large datasets. Strong experience with Databricks (or equivalent Spark/Hive-based lakehouse platform) and Jupyter notebooks for building and orchestrating data pipelines. Expertise with relational databases (Oracle, SQL Server) with experience in schema design and dimensional data modeling. Experience leveraging RESTful web services to collect and publish data. Experience in software engineering development and testing life cycles using but not limited to dotnet, Python, R, Linux, Java, JavaScript, Lambda, and SQL programming.

Education Desired: Bachelor’s degree in computer science, Mathematics, or other technical field or equivalent work experience.

Job Responsibilities

Develop and implement end-to-end complex data projects and technical solutions through translating business requirements into technical solutions and data-flow architectures.

Build and automate data pipelines that clean, transform, and aggregate unorganized data into data sources that are ready for analysis.

Use expertise to apply various analytic methods to discover and interpret information about supply chain operations — receiving, warehouse throughput, transportation, and inventory — from multiple data sources to implement analytics solutions.

Use expertise in database design to tap into data across warehouse management, transportation management, fleet management, delivery scheduling, and store/retail systems — aggregating it into a unified databricks lakehouse that powers faster decisions and KPIs for business teams.

Design, implement, and deploy data applications and mechanisms using big data technology.

Provide subject matter expertise for multiple projects concurrently through all phases of the development lifecycle.

Develop, enhance, govern, and administer the supply chain data platform to: collect, transform, enrich, unify, and integrate data across distribution centers and transportation systems.

Work collaboratively with IT teams, warehouse and transportation teams, analytics teams, and business leaders to ensure actionable insight is provided to key stakeholders.

Research and analyze supply chain operational data to improve service levels and cost-to-serve.