Job highlights
Identified by Google from the original job post
Qualifications
7+ years of proven experience in Data Engineering or Business Analytics roles working with ETL, Data Modeling, and Data Architecture, developing modem data pipelines and applications
Expertise crafting and implementing enterprise data pipelines using data engineering approaches and tools including but not limited to: Spark, PySpark, Scala, Docker, Databricks, Glue, cloud-native EDW (Snowflake, Redshift), Kafka, Athena
Strong dimensional data modeling (Star, Snowflake) and ER modeling skills
Proficiency building and maintaining infrastructure-as-code preferably with terraform and AWS ecosystem
Proficiency in Java, Python, SQL
Experience with writing and reviewing version-controlled code (GitHub)
Experience optimally presenting insights and summarizing sophisticated data to diverse audiences through visualizations
To be a self-starter with the ability to take initiative and drive projects forward independently
Experience working with and delivering to collaborators from multiple parts of the company
Some experience with API development
Some experience with technologies like GraphQL, graph databases
Responsibilities
This person will be part of the Customer Interaction Datastore team responsible for building a customer data platform in support of critical Enterprise Priorities
The ideal candidate will have an interest in building data pipelines, an eye for data quality, and potentially a curiosity about or experience building APIs
Additionally, the candidate will have a strong customer first, embody a curious and think big approach to their work to help further innovation within the team, and be an engaged and respectful team member
Develop and maintain complex data ingestion pipelines and transformations for data originating from multiple data sources (structured/unstructured)
Assist in crafting proof of concepts and advise, consult, mentor, and coach other data engineering and analytics professionals on data standards
Data cataloging and documentation of data sources
Supervise data pipelines for accuracy, missing data, enhancements, changes, and billing volumes to ensure all data is assembled and processed accurately and when needed
Build containerized applications with microservices architecture
Reconcile data issues and alerts between various systems, finding opportunities to innovate and drive improvements
Work with multi-functional partners in defining and documenting requirements for building high-quality and impactful data products
Create operational reports using visualization/business intelligence tools
Job description
Our Opportunity:

Chewy is seeking a Data Engineer III in Boston or Minneapolis. This person will be part of the Customer Interaction Datastore team responsible for building a customer data platform in support of critical Enterprise Priorities. The ideal candidate will have an interest in building data pipelines, an eye for data quality, and potentially a curiosity about or experience building APIs. Additionally, the candidate will have a strong customer first, embody a curious and think big approach to their work to help further innovation within the team, and be an engaged and respectful team member.

What You’ll Do:
• Develop and maintain complex data ingestion pipelines and transformations for data originating from multiple data sources (structured/unstructured)
• Assist in crafting proof of concepts and advise, consult, mentor, and coach other data engineering and analytics professionals on data standards.
• Data cataloging and documentation of data sources
• Supervise data pipelines for accuracy, missing data, enhancements, changes, and billing volumes to ensure all data is assembled and processed accurately and when needed
• Build containerized applications with microservices architecture
• Reconcile data issues and alerts between various systems, finding opportunities to innovate and drive improvements.
• Work with multi-functional partners in defining and documenting requirements for building high-quality and impactful data products.
• Create operational reports using visualization/business intelligence tools.

What You’ll Need:
• 7+ years of proven experience in Data Engineering or Business Analytics roles working with ETL, Data Modeling, and Data Architecture, developing modem data pipelines and applications
• Expertise crafting and implementing enterprise data pipelines using data engineering approaches and tools including but not limited to: Spark, PySpark, Scala, Docker, Databricks, Glue, cloud-native EDW (Snowflake, Redshift), Kafka, Athena
• Strong dimensional data modeling (Star, Snowflake) and ER modeling skills
• Proficiency building and maintaining infrastructure-as-code preferably with terraform and AWS ecosystem
• Proficiency in Java, Python, SQL
• Experience with writing and reviewing version-controlled code (GitHub)
• Experience optimally presenting insights and summarizing sophisticated data to diverse audiences through visualizations.
• To be a self-starter with the ability to take initiative and drive projects forward independently.
• Experience working with and delivering to collaborators from multiple parts of the company.

Bonus:
• Some experience with API development
• Some experience with technologies like GraphQL, graph databases

Chewy is committed to equal opportunity. We value and embrace diversity and inclusion of all Team Members. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact [email protected].

If you have a question regarding your application, please contact [email protected].

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