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Manager, Data Engineering

Our Opportunity:

Chewy is growing! We are looking for a Manager, Data Engineering (Data Engingeer III), to join the pack. In this role, you will maximise your extensive expertise in data engineering will be integral in building and maintaining high-quality data pipelines that enable development of insights, data visualization, models and other analytical products. To deliver this, you will develop and implement advanced data products and technologies that scale to meet the needs of our evolving business. Our fast-paced environment presents continuous new challenges and opportunities. Does this sound like you? If so, we would love to hear from you!

What You'll Do:

  • Implement the strategy, design, execution, system configuration of our promotion and ordering data
  • Monitor data pipelines for accuracy, missing data, enhancements, changes, and billing volumes to ensure all data is collected and processed accurately and when needed.
  • Work with multi-functional partners in defining and documenting requirements for building high-quality and impactful data products
  • Reconcile data issues and alerts between various systems, finding opportunities to innovate and drive improvements
  • Lead the evaluation, implementation, and deployment of emerging tools and technologies to improve our productivity as a team.
  • Develop and deliver communication and education plans on data engineering capabilities, standards, and processes.
  • Code, test, and document new or modified data systems to create robust and scalable applications for reporting and data analytics.
  • Own and document data pipelines, monitoring, data accuracy and data lineage
  • Lead a team of Data Engineers as a player-coach, setting the team up for success while being an important contributor as well.

What You'll Need:

  • Bachelor’s degree in Computer Science, Computer Engineering, or related field and 5+ years of experience developing Data Integration solutions required, or equivalent levels of relevant education and experience.
  • This position requires tried experience in data warehousing practices and concepts as well as validated experience in dimensional and relational database modeling.
  • 5+ years of Data Engineering experience focused on Data Modeling, Data Architecture, and Developing modern data pipelines and applications for reporting and analytics.
  • Experience in working with retail data is a huge plus.
  • 3+ years of professional Python experience.
  • Experience in SQL, data warehouse, performance tuning, and ETL pipelines using AWS Glue, Control M, Pyspark, DBT and others.
  • Experienced with setting up end-to-end data pipelines in an enterprise environment.
  • Experience with Infrastructure, Scripting, and Architecture is very beneficial.
  • Hands-on with Cloud computing technology like AWS, Google Cloud, etc.
  • Experience with developing solutions for cloud computing services and infrastructure with AWS (S3, Athena, Glue, Lambda)
  • Experience in Tableau, Looker, or similar visualization/business intelligence platform
  • Ability to effectively operate both independently and as part of a team.
  • Self-motivated with strong problem-solving and self-learning skills.
  • E-com, Retail, or startup experience is a plus.
  • 3+ years leading a team of data engineers
  • The position may require travel

Bonus:

  • PyTorch, JavaScript, D3.js & Restful API’s
  • Snowflake, Vertica, Postgres, etc.
  • Exposure to Apache Airflow or other DAG or equivalent experience frameworks
  • Expertise in designing and implementing data pipelines using modern data engineering approaches and tools: Spark, PySpark, Java, Docker, cloud-native DWH (Snowflake, Redshift), Kafka/Confluence, etc.
  • Experience with CI/CD processes and platforms.

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 CAAR@chewy.com.

 

If you have a question regarding your application, please contact HR@chewy.com.

 

To access Chewy's Customer Privacy Policy, please click here. To access Chewy's California CPRA Job Applicant Privacy Policy, please click here.

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What You Should Know About Manager, Data Engineering, Chewy

Chewy is on the move, and we’re searching for a passionate Manager, Data Engineering to join our dynamic team in Boston, Massachusetts. If you possess deep expertise in data engineering and are eager to make a tangible impact, this role is perfect for you! Here, you’ll be pivotal in constructing and maintaining high-quality data pipelines, which drive insights, enhance data visualizations, and power analytical products. You’ll take charge of making strategic decisions regarding promotion and ordering data, ensuring accuracy while keeping your eyes peeled for opportunities to innovate. You’ll collaborate with cross-functional teams to define what high-quality data products look like and take charge of troubleshooting any data issues or alerts. Plus, you'll lead a talented team of Data Engineers, acting as a mentor and key contributor to foster their success. With your background in data warehousing, dimensional modeling, and a minimum of 5 years of Data Engineering experience under your belt, you’ll be ready to dive deep into modern data pipelines. We love seeing candidates with cloud computing experience, especially within AWS or Google Cloud, come aboard! If you thrive in fast-paced environments and are driven by problem-solving, we’d love to talk to you about how you can further Chewy’s mission. Join us and contribute to something special!

Frequently Asked Questions (FAQs) for Manager, Data Engineering Role at Chewy
What are the responsibilities of a Manager, Data Engineering at Chewy?

As the Manager, Data Engineering at Chewy, your responsibilities include implementing data strategies, monitoring the accuracy of data pipelines, collaborating with multi-functional teams, reconciling data issues, and leading your team of Data Engineers. You'll also be involved in developing advanced data products and educating others about data engineering capabilities.

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What qualifications are needed for the Manager, Data Engineering position at Chewy?

To qualify for the Manager, Data Engineering role at Chewy, you need a Bachelor’s degree in Computer Science or related fields along with 5+ years of experience in developing Data Integration solutions. Additionally, experience in data warehousing, data modeling, and cloud computing skills are essential for success in this position.

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Is experience in retail data crucial for the Manager, Data Engineering position at Chewy?

Yes, working with retail data is highly advantageous for the Manager, Data Engineering position at Chewy. Having a background in e-commerce or retail can significantly enhance your contributions in this role, as it requires a deep understanding of data integration practices relevant to the retail sector.

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What tools and technologies should a Manager, Data Engineering at Chewy be familiar with?

A Manager, Data Engineering at Chewy should be well-versed in various tools and technologies including SQL, ETL tools like AWS Glue, Pyspark, and data visualization platforms such as Tableau or Looker. Familiarity with cloud services like AWS and Google Cloud is also highly preferred.

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What are the growth opportunities for a Manager, Data Engineering at Chewy?

At Chewy, a Manager, Data Engineering can expect ample growth opportunities. You’ll lead a talented team, work on innovative projects, and have the chance to continually expand your skills in modern data engineering technologies. The fast-paced environment presents diverse challenges that will help you advance in your career.

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Common Interview Questions for Manager, Data Engineering
Can you explain your experience with data pipelines and the technologies you've used?

In your response, outline specific projects where you implemented data pipelines. Describe the technologies you used, such as AWS Glue or Pyspark, and how you ensured the accuracy and efficiency of these pipelines.

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How do you approach troubleshooting data accuracy issues?

Discuss your process for identifying and resolving data inaccuracies. This might involve monitoring data systems, collaborating with team members to define issues, and developing solutions based on your findings.

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What strategies do you use for team leadership and fostering success?

Provide examples of how you’ve led teams in the past, including setting goals, providing mentorship, and encouraging collaboration among team members. Highlight your approach to creating a positive work environment.

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How do you keep up with the latest developments in data engineering?

Discuss how you stay current with trends by attending conferences, following relevant publications, or participating in online communities. You can also mention specific areas you are currently exploring.

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What is your experience with cloud computing technologies?

Share specific examples of projects where you utilized cloud computing, especially AWS or Google Cloud. Discuss your role and any notable accomplishments that resulted from leveraging those technologies.

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Describe your experience with data warehousing practices.

Talk about your knowledge of data warehousing concepts. Be prepared to discuss how you’ve implemented these practices in previous roles and the impacts they had on data management and analytics.

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What methods do you use for data modeling?

Explain your approach to data modeling, including techniques you’ve applied, tools you’ve used, and successful modeling outcomes you achieved in past projects.

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Can you give an example of a challenging data engineering problem you faced and how you solved it?

Provide a detailed account of a specific challenge, the steps you took to resolve it, and the outcome. This demonstrates your problem-solving abilities and experience in the field.

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What collaboration tools and practices do you prefer in a team setting?

Discuss the tools you use for collaboration, such as project management software or communication platforms, and explain how these tools improve your team's efficiency and effectiveness.

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How would you handle a scenario where a project's data requirements change mid-development?

Describe your flexible approach to managing changing data requirements, emphasizing communication with stakeholders, adapting the data pipeline, and ensuring timely delivery of the project despite the changes.

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At Chewy, our mission is to be the most trusted and convenient destination for pet parents and partners, everywhere.

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Full-time, on-site
DATE POSTED
April 2, 2025

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