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Data Engineer III
1 month ago
Our Opportunity:
Chewyâs Merch Analytics Team is looking for a Senior Data Engineer (Data Engingeer III), to join the pack. In this role, you will leverage 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.
What You'll Do:
- Implement the strategy, design, execution, system configuration of our autoship and ordering data
- Monitor data pipelines for accuracy, missing data, enhancements, changes, and billing volumes to ensure all data is captured and processed accurately and when needed.
- Work with cross-functional stakeholders 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
What You'll Need:
- Bachelorâs 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 proven experience in data warehousing practices and concepts as well as proven 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 marketing data is a huge plus.
- 3+ years of professional Python experience.
- Experience in SQL, data warehouse, performance tuning, and ETL pipelines using AWS Glue, Pyspark, 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.
- The position may require travel
Bonus:
- PyTorch, JavaScript, D3.js & Restful APIâs
- Snowflake, Vertica, Postgres, etc.
- Exposure to Apache Airflow or other DAG frameworks
- MarTech Knowledge
- Media Mix Modelling and Marketing Attribution hands-on experience.
- Understanding of link tracking, pixels/tags, Google Analytics, and marketing attribution
- 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.
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