Our Opportunity:

Chewy’s Planning and Analytics team has an exciting opportunity for a Data Engineer II to join the pack. With a background in data engineering, data analysis and reporting you will be a part of a team responsible for operational and tactical reporting generating insights to grow Customer Service operations and planning. This includes building high quality data pipelines that drives analytic solutions and creating data products for analytics and data scientist team members to improve their productivity. Our organization is a fast-paced environment with new challenges and new opportunities each day. You will be responsible for building and implementing data products and technologies which will handle the growing business needs and play a key role in redefining what it means to be a world-class customer service organization.

What You'll Do:

• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
• Solve complex data problems to deliver insights that helps our business to achieve their goals.
• Create data & forecasting products by working with analytics and data scientist team members to speed to market and to enrich data and model options.
• Assist in creating Proof of Concepts and advise, consult, mentor and coach other data and analytic professionals on data standards and practices.
• Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering to improve our productivity as a team.
• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
• Code, test, and document new or modified data systems to create robust and scalable applications for data analytics.
• Partner with Business Analysts and Solutions Architects to develop technical architectures for strategic enterprise projects and initiatives.
• Document technical details of your work using industry standard protocols like Jira, Confluence etc.
• Respect for Teammates – encouraging diverse identities, backgrounds, talent and perspectives.
• Collaboration – working with all team members, and across teams, to integrate perspectives and encourage contributions.
• Adaptability – quickly applying feedback and circumstances to team priorities.

What You'll Need:

• Bachelor of Science or Master’s degree in Computer Science, Engineering, Information Systems, Mathematics or related field
• 7+ years of enterprise experience as a data engineer and/or software engineer
• Strong software development skills in Python and Advanced SQL, tuning SQL queries and data pipelines
• Proven ability to demonstrate developing modern data pipelines and applications for analytics (e.g., BI, reporting, dashboards) and advanced analytics (e.g., machine learning, deep learning) use cases.
• Knowledge of industry best practices, strong understanding how data is extracted, transformed, scrubbed, and loaded in a large Data Warehouse environment.
• 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.
• Excellent written and oral communication skills and ability to work with development teams.

Bonus:

• Exposure building dimensional models in the data warehouse
• Experience with MPP/Columnar databases like Snowflake, Redshift, etc
• Exposure to data streaming tools and technologies like kafka or similar technologies
• Experience with developing solutions on cloud computing services and infrastructure with AWS
• AWS Components like EC2, S3, Athena, Lambda etc
• Experience with Sagemaker/Sagemaker Studio
• AWS Certified Developer/AWS Machine Learning
• 4+ years of experience building data integrations and pipelines from data lake, APIs, relational databases, and third-party systems
• 2+ years of experience working with workflow orchestration tools (Preferred: Airflow, Prefect, Luigi, AutoSys)
• Experience designing and building infrastructure in cloud data environments (Preferred: AWS, GCP, Azure)