Senior Data & AI Platform Engineer

About This Opportunity

We are representing a confidential SaaS organization in Denmark that is entering a critical scaling phase. Our client needs a senior platform engineer to modernize their data foundation and enable AI-powered decision-making across executive reporting, finance, product analytics, and business intelligence.

This is a hands-on leadership role. You will own the migration from legacy systems into a governed cloud data platform, maintain business-critical reporting, and apply AI and automation to accelerate data engineering workflows. You'll set technical standards, mentor engineers, and ensure the platform supports rapid growth and future acquisitions.

Core Responsibilities

• Lead hands-on Microsoft Fabric architecture across lakehouse, warehouse, notebooks, semantic models, Git-backed delivery, and production governance
• Drive migration from legacy reporting and metric tooling into a governed semantic layer, including parity testing, stakeholder sign-off, and safe decommissioning
• Own and improve data pipelines across APIs, files, events, and operational stores; establish robust orchestration, monitoring, alerting, data-quality checks, and incident response
• Use AI and automation to accelerate ETL/ELT development, data mapping, documentation, testing, report generation, monitoring, and data-quality management
• Design high-quality Power BI semantic models, DAX measures, and reusable metric definitions for leadership, finance, commercial, product, marketing, and operations reporting
• Support CRM and operational data integrations, including outbound data feeds, identity mapping, schema mapping, reverse-ETL patterns, and monitoring
• Create reliable ingestion and modelling patterns for acquired businesses, so future integrations are repeatable, auditable, and faster to execute
• Set data-engineering standards: definition of ready/done, code review, release discipline, documentation, runbooks, and platform change governance
• Mentor engineers and analysts; translate business-critical data needs into pragmatic technical delivery
• Build automated reporting and insight-generation capabilities that reduce manual analysis and improve decision speed

What We're Looking For

Must-Have Requirements:

• 6+ years in modern data warehousing, analytics engineering, or data platform engineering, ideally in SaaS, marketplace, fintech, payments, e-commerce, or multi-region B2B2C environments
• Strong Microsoft Fabric capability, or deep Azure Synapse / Databricks experience with clear ability to specialize quickly in Fabric
• Expert SQL/T-SQL plus strong Python or PySpark, with a track record of building maintainable ELT/ETL pipelines and analytical data models
• Strong Power BI and DAX experience, including semantic modelling, incremental refresh, performance tuning, model governance, and capacity/cost awareness
• Experience leading legacy-to-modern data platform migrations, including metric parity, stakeholder validation, change control, and safe decommissioning
• Experience operating production data systems: monitoring, alert design, incident triage, root-cause analysis, data-quality checks, lineage, and runbooks
• Comfortable with Git-based data engineering workflows, pull requests, release discipline, and standards for notebooks, pipelines, and semantic model changes
• Practical experience using AI or automation to improve data engineering, reporting, documentation, testing, monitoring, migration, or developer productivity

Strong-to-Have Experience:

• Payments, settlement, reconciliation, fees, chargebacks, merchant reporting, or finance-domain data
• CRM-side data flows and reverse-ETL patterns, especially HubSpot, Salesforce, Zendesk, or similar platforms
• M&A or acquired-company data integrations: schema discovery, file/API ingestion, data profiling, master-data mapping, migration QA, and reporting continuity
• NoSQL-to-analytics modelling, including change-feed patterns from operational databases into lakehouse or warehouse structures
• GA4, BigQuery export, Google Ads / SEM feeds, Segment, or other event and marketing analytics sources
• Experience with Azure OpenAI, LLMs, RAG, AI agents, prompt/version management, or AI-assisted development workflows
• Experience building AI-generated reporting, natural-language analytics, business copilots, automated insight generation, or customer intelligence tools
• Responsible AI and governance experience, including RBAC, PII handling, audit logs, human approval flows, explainability, and GDPR-conscious design

What Sets Great Candidates Apart:

• You have owned a production data platform, not only built dashboards or one-off analytics projects
• You can explain how you governed metrics and prevented conflicting definitions across teams
• You have migrated or consolidated legacy reporting into a modern semantic layer without breaking business trust
• You balance delivery urgency with reliability, documentation, cost control, and operational resilience
• You communicate clearly with executives, product teams, analysts, and engineers; you can say "no" or "not yet" with evidence
• You are hands-on enough to debug pipelines and models, while senior enough to set standards and mentor others
• You have used AI or automation in a real data-engineering context to speed up delivery, not just as a novelty, and can describe the guardrails you put around it

How We Work With You

When you apply through Get A Job.ai, our talent team will conduct an initial screening to understand your background and match it to our client's needs. If there's a strong fit, we'll submit your profile to the client for consideration. Throughout the process, we act as your advocate and liaison.

Please apply exclusively through Get A Job.ai and do not contact the client directly. All communication and coordination will be managed by our recruiting team to ensure a smooth, professional experience for everyone involved.

Pay

Compensation details will be discussed during the screening process and are determined by the client based on experience, location, and market conditions.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome applications from candidates of all backgrounds and work to ensure fair, equitable access to opportunities.