Senior Data, AI Platform Engineer

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

📋 Description

• Design, construct, and manage production-grade data solutions utilizing Microsoft Fabric across Lakehouse, Warehouse, notebooks, pipelines, and associated platform functionalities.

• Develop and maintain production pipelines in Fabric, Python, and PySpark that are rigorously tested and easily maintainable.

• Create ingestion and transformation methodologies that can scale across various source systems, databases, and business domains while managing the impact on sources, concurrency, and platform costs.

• Oversee Fabric capacity and costs, and phase out unnecessary legacy components.

• Spearhead migrations from legacy systems to modern platforms, ensuring metric parity, stakeholder approval, change management, and safe decommissioning processes.

• Operate the platform in a production environment through monitoring, alerting, incident triage, root-cause analysis, data quality assessments, lineage tracking, and runbooks.

• Troubleshoot and resolve production issues related to SQL, Spark, pipelines, and semantic models.

• Collaborate with analytics and business stakeholders to support and enhance governed semantic models and reusable metric definitions.

• Integrate AI into the platform and delivery using RAG, Azure OpenAI, and agents, focusing on prompt and version management.

• Provide applied data science solutions such as churn analysis, recommendations, personalization, fraud detection, or risk models, and demonstrate their effectiveness.

• Collaborate with executives, Finance, Product, and engineering teams to make informed decisions regarding speed, standardization, automation, and control.

⛳️ Requirements

• A minimum of 6 years of relevant data experience, including significant recent hands-on responsibilities in data engineering or data-platform engineering within production settings.

• Proven capability to independently navigate a data engineering challenge from requirements gathering and technical design through to implementation, production deployment, monitoring, and ongoing maintenance.

• Extensive hands-on experience with Microsoft Fabric, or strong familiarity with Synapse, Databricks, or Delta, showing a clear pathway to Fabric proficiency.

• In-depth knowledge of lakehouse architecture and Delta-centric data engineering, encompassing partitioning, schema evolution, file optimization, and performance considerations.

• Proficient in SQL and T-SQL, including complex modeling and performance tuning.

• Expertise in production-grade Python or PySpark.

• Extensive experience in designing and implementing incremental data ingestion patterns, utilizing methods such as CDC, change tracking, or watermarks, ensuring reliable merge/upsert, replay, and idempotent processing.

• Familiarity with analytical and semantic data modeling, ideally with Power BI/Fabric semantic models, emphasizing performance optimization, governance, and reusable business metrics.

• Basic understanding of Azure platform essentials, including Azure SQL, ADLS/OneLake, Entra ID, managed identities, RBAC, and Key Vault.

• A successful history of leading legacy-to-modern migrations.

• Tangible hands-on AI engineering experience beyond standard out-of-the-box Copilot features.

• Specific data science or ML models that you have implemented, accompanied by measurable results.

• Strong expertise in Power BI/Fabric, including Direct Lake, DAX, semantic model performance optimization, incremental refresh strategies, and capacity considerations.

• Experience with Infrastructure-as-Code using Terraform, Bicep, or similar tools.

• Background in data platforms within SaaS, marketplace, fintech, payments, e-commerce, or multi-region enterprises.

🏝️ Benefits

• A fully remote position, complemented by quarterly in-person meetings at one of our global offices.

• Responsibility for a critical business data and AI platform.

• A cooperative, international engineering team environment.