Data Engineer at the Dow Delivery Center at UIUC (Champaign, IL)

At Dow, we believe in putting people first and we’re passionate about delivering integrity, respect and safety to our customers, our employees and the planet.  

Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We’re a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you’re looking for a challenge and meaningful role, you’re in the right place. 

About you and this role

Dow has an exciting opportunity for a Data Engineer on the Data & Analytics Platforms team within our Enterprise Data & Analytics organization.

**This position is located full-time on site at the Dow Delivery Center in University of Illinois Research Park in Champaign, IL.**

As a Data Engineer specializing in data and analytics solutions, you will work with a diverse cross-functional team whose objective is to deliver solutions that drive business value for Dow. Recent solutions include carbon visibility, plastics circularity, and sales opportunities utilizing our enterprise data ecosystem. In this role, you will focus on ingestion, persistence, and curation of data as defined by specific projects. As this is a research park role, part of the expectation of this role will be to manage the onboarding process and provide ongoing coaching of college interns.  You will work closely with a global, multi-disciplinary team to:   

• Create data pipelines for projects in the Azure environment.
• Design, develop, test, and implement analytic and reporting solutions. This includes the curation and ingestion of data from different source systems, driving end to end data flow for multiple solutions.
• Identify opportunities for innovating with digital capabilities aiming to accelerate Dow’s digital transformation.  

Responsibilities

• Owns the development and deployment of solutions enabling data ingestion, storage, and consumption across Dow's enterprise data platforms (Azure based) . 
• Develops and deploys scalable and efficient data processing pipelines using Azure Data Factory, Azure Databricks, and other relevant technologies.  
• Collaborates with data scientists and data analysts to support their data needs.  
• Continuously monitors, tests, and improves data architecture and performance . 
• Deploys Azure services using Infrastructure as Code and Azure DevOps. 
• Manage the onboarding process and ongoing coaching of college interns.

Qualifications

• A minimum of a Bachelor's degree, or 5 years relevant experience, or relevant military experience at or above a U.S. E6 or Canadian Petty Officer 2nd Class or Sergeant ranking.
• A minimum of 2 years of professional data platform experience (data ingestion, pipeline orchestration).
• A minimum of 2 years of professional experience in Databricks technology.
• Experience in Microsoft Azure’s Environment setting up Azure Databricks data processing workloads, experience with deploying Machine Learning models for predictive analytics, setting up containerized applications, and utilizing various authentication methods for application consumption.
• A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process.

Preferred Skills - having some of these skills will be beneficial but can be learned on the job

• A degree discipline in Computer Science, Information Technology, or other Engineering disciplines.
• Ability to thrive in challenging situations and solve complex problems .  
• Manage own work effort in multiple projects with little supervision.  
• Interested about emerging technologies with the ability to quickly learn and exploit cutting edge offerings to achieve business objectives.
• Data Management and Storage: Proficiency with Azure SQL Database, Azure Data Lake Storage, Azure Cosmos DB, and Azure Blob Storage.
• Data Integration and ETL: Experience with Azure Data Factory for developing and implementing ETL processes.
• Big Data and Analytics: Knowledge of Azure Databricks, Apache Spark, and other big da