How we LEAD:
We are seeking an experienced and driven Senior Data Engineer Enterprise Data Products within the Global Data & Analytics team.
You are passionate about building scalable, reliable, and AI-ready data platforms that power enterprise decision-making and advanced analytics. You understand that modern data platforms must not only support reporting, but also enable machine learning, generative AI, and intelligent applications through high-quality, well-governed, and semantically consistent data.
In this role, you will lead teams of data engineers responsible for building and operating domain-specific data products, semantic layers, and data marts that serve as trusted, AI-ready sources of truth across the organization, with a strong emphasis on ecommerce data products and Shopify data pipelines.
You will play a key role in shaping how data is structured, governed, and exposed to support AI/ML use cases, feature engineering, and semantic consistency across tools and applications.
How youll CREATE:
Design and build scalable data pipelines and data products that support analytics and AI/ML use cases.
Build and scale ecommerce data products and pipelines, with particular focus on Shopify data such as orders, customers, products, transactions, fulfillment, and marketing events.
Develop and maintain AI-ready datasets, ensuring high quality, consistency, and usability for downstream applications.
Work with data scientists and analysts to support feature engineering, model training data, and experimentation needs.
Contribute to building and maintaining semantic layers that standardize business definitions and enable consistent reporting and analysis.
Implement data validation, testing, and monitoring to ensure data quality and reliability.
Build and optimize data models (dimensional, curated layers) aligned with business requirements.
Optimize data storage and query performance by leveraging columnar data structures and databases where applicable.
Support batch and real-time data pipelines using modern data stack tools.
Follow best practices for code quality, version control, and CI/CD in data engineering workflows.
Collaborate with product, analytics, and governance teams to ensure data is well-documented, discoverable, and trusted.
Troubleshoot and resolve data issues, ensuring minimal disruption to downstream users.
Bring your VIBE:
58 years of experience in data engineering or related roles.
Strong experience building data pipelines, data models, and data platforms.
Experience working with Shopify data is strongly preferred, including Shopify orders/customers/products/fulfillment schemas
Proven experience handling ecommerce data at scale, including orders, carts, customers, product/catalog, inventory, fulfillment, payments, refunds/returns, promotions/discounts, subscriptions, web/app clickstream, and marketing attribution.
Preferred: experience handling Shopify data and ecommerce datasets, including ingesting, modeling, validating, and reconciling commerce data across platforms.
Familiarity with AI/ML data requirements, including preparing datasets for model training and analytics.
Hands-on experience working with or contributing to semantic layers (e.g., dbt, LookML, etc.).
Solid understanding of data warehousing, dimensional modeling, and modern data architectures.
Experience with cloud platforms (AWS, Azure, or GCP) and tools like Spark, Snowflake, Databricks, or similar.
Strong SQL skills and proficiency in Python or similar language.
Experience working with columnar databases or columnar storage formats (e.g., BigQuery, Redshift, Snowflake, Parquet) and optimizing query performance.
Experience implementing data quality checks and monitoring.
Ability to work cross-functionally and translate requirements into technical solutions.
Preferred candidate location: Philadelphia, PA (Philly).
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