Senior Data Platform Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Take charge of the continuity and advancement of OrderYOYO’s modern data platform during a pivotal scaling phase.

• Spearhead the transition from outdated reporting and metric tools to a regulated Microsoft Fabric platform.

• Ensure the reliability of business-critical BI and semantic models.

• Enhance the stability and monitoring of data pipelines.

• Facilitate CRM data integration.

• Provide senior technical guidance for data engineering initiatives.

• Design high-quality Power BI semantic models, DAX measures, and reusable metric definitions for reporting in leadership, finance, commercial, product, marketing, payments, and support.

• Establish consistent ingestion and modeling patterns for acquired businesses, ensuring that future integrations are repeatable, auditable, and executed more swiftly.

• Mentor engineers and analysts while translating vital business data requirements into practical technical solutions.

⛳️ Requirements

• Over 6 years of experience in modern data warehousing, analytics engineering, or data platform engineering, preferably in a SaaS, marketplace, fintech, payments, e-commerce, or multi-region B2B2C setting.

• Proficient in Microsoft Fabric, or possess extensive experience with Azure Synapse / Databricks, with the ability to quickly specialize in Fabric.

• Expert in SQL/T-SQL, along with strong skills in Python or PySpark, demonstrated through a history of developing maintainable ELT/ETL pipelines and analytical data models.

• Strong background in Power BI and DAX, encompassing semantic modeling, incremental refresh, performance tuning, model governance, and cost/capacity awareness.

• Experience in leading migrations from legacy to modern data platforms, including metric parity, stakeholder validation, change control, and safe decommissioning.

• Familiarity with operating production data systems, including monitoring, alert design, incident triage, root-cause analysis, data-quality checks, lineage, and runbooks.

• Comfortable with Git-based data engineering workflows, including pull requests, release discipline, and standards for notebooks, pipelines, and changes to semantic models.

🏝️ Benefits

• Competitive salary

• Growing international company

• Growth opportunities