Senior Data & AI Platform Engineer

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

📋 Description

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

• Develop and operate production pipelines using Fabric, Python, and PySpark.

• Create ingestion and transformation patterns across diverse source systems, databases, and business sectors.

• Oversee Fabric capacity and expenses while phasing out obsolete legacy components.

• Lead transitions from legacy systems to modern platforms, ensuring metric parity, stakeholder approval, change management, and secure decommissioning.

• Operate the platform in a production environment through monitoring, alerting, incident management, root cause analysis, data quality assessments, lineage tracking, and runbook creation.

• Identify and resolve production issues across 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, incorporating prompt and version management.

• Deliver practical data science applications such as churn predictions, recommendations, personalization, fraud detection, or risk modeling, and present the findings.

• Collaborate with executives, Finance, Product, and engineering teams to make informed platform and delivery decisions.

⛳️ Requirements

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

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

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

• Strong comprehension of lakehouse architecture and Delta-based data engineering, including partitioning, schema evolution, file optimization, and performance considerations.

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

• Experience with production-level Python or PySpark.

• Significant experience in designing and implementing incremental data ingestion patterns, including methodologies such as CDC, change tracking, or watermarks, with reliable merge/upsert, replay, and idempotent processing.

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

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

• Proven track record of leading a transition from legacy systems to modern platforms.

• Real-world AI engineering experience beyond standard Copilot capabilities.

• Tangible data science or ML models you have delivered, along with measurable outcomes.

• Strong Power BI/Fabric expertise, including Direct Lake, DAX, performance tuning of semantic models, incremental refresh, and capacity management.

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

• Data platform experience in SaaS, marketplace, fintech, payments, e-commerce, or multi-region businesses.

🏝️ Benefits

• Quarterly team gatherings at one of our global offices.

• A remote work opportunity.

• Responsibility for a critical business data and AI platform.

• A collaborative, international engineering team.