Senior Data Engineer

Our Opportunity:

Chewy is looking for a Marketing Senior Data Engineer, Marketing Technology to join the Marketing Science & Operations team in Plantation, FL or Boston, MA or Seattle, WA, or Minneapolis, MN. This role is responsible for creating and deploying the data pipelines and platform integrations to enable the Marketing teams. This role owns all Marketing data from end-to-end, including data ingestion, transformation, visualization, and data architecture to ensure best-in-class operational reliability and modularity. These data solutions optimize our media investment and efficacy of content for both paid media and customer engagement programs.

What You'll Do:

• Implement the strategy, design, execution, system configuration, and operations of the business's marketing databases that help marketers in data-driven decision making
• 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
• Deploy, evaluate, and refine data pipelines for ML/DS models at scale in a production environment.
• Explore structured/unstructured data sources to build a robust feature store to help scale model building process

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 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 API’s
• 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.