Data Engineer - Microsoft Fabric

🚀 What We Do

• Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
• Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
• Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships

• Amazon Web Services
• Astronomer
• Databricks

🌟 Our Values

• 📊 We are Data Nerds
• 🤗 We are Open Team Players
• 🚀 We Take Ownership
• 🌟 We Have a Positive Mindset
 
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀

Responsibilities 🤓

• Own end-to-end pipeline reliability across Bronze, Silver, and Gold layers (PySpark + Delta Lake on Microsoft Fabric). 
• Build and maintain ingestion notebooks for new retailers and syndicated data partners as we scale.
• Harden existing pipelines - idempotent replaceWhere patterns, partition strategies, ZORDER optimization, schema enforcement, and dedup logic.
• Run and improve our daily and weekly orchestration through Fabric Data Pipelines and scheduled notebook runs.
• Diagnose and resolve runtime issues across the medallion stack - including the parts of Fabric that don’t behave the way the docs say they do.
• Manage lakehouse shortcuts, Azure Blob Storage accounts (for non-HNS sources), and data source authentication via Entra / Key Vault.
• Partner with the AI engineering team to keep the Gold layer clean and queryable for our RAG, reporting, and attribution use cases.
• Contribute to data modeling decisions across our unified retailer schemas, keeping naming conventions consistent across the platform.
• Document patterns so the next engineer can move at our pace. 

Required Skills 💻

• 4+ years building data pipelines in production.
• Deep PySpark and Delta Lake experience - you’ve shipped real medallion architectures, not just read about them.
•  Hands-on Microsoft Fabric experience: lakehouses, notebooks, Data Pipelines, OneLake shortcuts. If you’ve worked through Fabric’s quirks (cells not reliably sharing Python variables, shortcut type limitations on non-HNS storage, etc.), that’s exactly the experience we want.
• Strong SQL, including window functions, CTEs, and analytical patterns. Comfortable reasoning about partition pruning and predicate pushdown.
• Comfortable owning end-to-end pipeline reliability - not just writing the happy path. You think about reruns, backfills, late-arriving data, and what happens at 4am when something breaks.
• Azure ecosystem familiarity: Blob Storage, Entra ID, Key Vault, Static Web Apps.
• Declarative, sparse code style. You prefer fixing the schema over patching the symptom.
• Strong written and spoken English; able to work effectively in a distributed team with overlap to North American business hours. 

🎁 Perks

• Remote-first culture – work from anywhere! 🌍
• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
• In-Company English Lessons.
• Birthday off + an extra vacation week (Mutt Week! 🏖️)
• Referral bonuses – help us grow the team & get rewarded!
• Maslow: Monthly credits to spend in our benefits marketplace.
• ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!