Data Engineer I

Our Opportunity:
Chewy is looking for a Data Engineer I to join our growing Transportation Systems team. You will get to work side by side with hard-working, passionate, and motivated engineers. You will have the opportunity to gain hands-on experience in the field of data engineering, working on different projects building data pipelines, ETL processes, and data warehouse management. The ideal candidate should have a strong interest in building and maintaining cloud databases, ingesting data using a variety of methods (including non-SQL technologies like SOAP and REST) and working on joining datasets from different cloud-based source systems in a centralized database. If you are equally as passionate about supply chain, transportation, management information systems, e-commerce, and career growth, an opportunity at Chewy may be a match! 

What You'll Do:

• Develop and Maintain data pipelines to extract, transform, and load (ETL) data from various sources into our data lake.
• Configure custom data pipelines within Snowflake/AWS/Databricks for ingestion
• Maintain real-time alarming and debugging tools
• Design and implement solutions on a cloud platform using Infrastructure as code (Terraform)
• Maintain, support, and develop within the Supply Chain - Transportation Data Mart Snowflake instance, including code build/review, auditing, performance tuning, and security.
• Create and maintain technical user documentation and models for the Data Mart

What You'll Need:

• Bachelor of Science or equivalent experience in Computer Science, Engineering, Information Systems or related field.
• Excellent verbal and written communication skills and the ability to explain details of complex concepts to non-expert partners in a simple and understandable way.
• Strong knowledge of SQL and relational databases
• Python programming skills for data processing and pipeline development
• Experience with ETL (Extract, Transform, Load) processes
• Basic knowledge of data warehousing concepts
• Familiarity with cloud platforms (especially AWS services like S3, Lambda, Airflow)
• Version control experience (Git)

Bonus:

• Experience of translating ambiguous customer requirements into clear problem definitions and delivering them.
• Design and execution experience of analytical projects.
• Experience with Python data libraries (pandas, numpy)
• Some exposure to big data technologies (Hadoop, Spark)
• Understanding of data modeling