Sr. Data Analytics Engineer

Fabletics is seeking a Senior Data Analytics Engineer to enhance the data foundations of their Global Supply Chain and Merchandise Planning domains. The role involves designing and building scalable data models and pipelines while collaborating closely with various teams to translate business needs into effective data solutions.

Responsibilities:

• Integrate logistics and planning data: Bring logistics visibility data (ETAs, transit times) into Snowflake and connect it with PLM, ERP, and planning sources for accurate PO loading and freight/landed-cost estimates
• Build trusted, reusable data products: Connect disparate supply chain and merchandising datasets into curated data products across our data lake and EDW, with reliable, well-defined metrics that power self-serve analytics across teams
• Own data quality and integration integrity: Take ownership of data quality across fragmented upstream systems — building the monitoring and controls that keep critical feeds reliable and integrations healthy as the planning landscape evolves
• Model data using best practices: Apply established Data Warehousing methodologies, primarily Dimensional (Kimball) modeling
• Turn complexity into insight: Transform large, complex datasets into actionable insights, delivered in a consumable format for historical and predictive analysis
• Perform data governance: Handle technical stewardship, data classification, compliance, and security considerations
• Validate before release: Build data visualizations to trial and validate data products before releasing them to customers

Requirements:

• 6+ years of experience in a data or software-adjacent field, working with systems and data infrastructure at scale
• Experience designing and implementing mature data pipelines across a data lake and Enterprise Data Warehouse (EDW), using Dimensional (Kimball) modeling methodologies
• Experience integrating data across fragmented or disparate source systems into coherent, reliable data products
• Experience with ELT/ETL tooling and workflow orchestration (e.g., Apache Airflow)
• Strong experience with relational databases and SQL in an analytical context
• Experience with data exploration, visualization, and data storytelling
• Excellent written and spoken communication, with a proven ability to work with a wide range of both technical and non-technical stakeholders
• Highly skilled at writing and maintaining high-quality, reusable code, applying design patterns and meeting coding standards
• A pragmatic adopter of AI in your own work — you use LLMs and AI-assisted tooling to accelerate development, code review, documentation, and data exploration, with good judgment about where they help and where they don't
• Track record of independently owning complex, ambiguous data initiatives end-to-end — making the architectural decisions, setting standards, and influencing technical direction across teams
• Experience with Snowflake, Airflow and Tableau is preferred
• Familiarity with supply chain, logistics, or merchandise planning data and processes (e.g., POs, freight/landed cost, assortment, production, or capacity planning)
• Exposure to logistics visibility tools and/or merchandise and supply chain planning platforms
• Ideal candidate brings foundational AI literacy, including experience using generative AI tools, and a proactive mindset to experiment with new technologies to drive productivity and innovation