Lead Data & AI Platform Engineer

OrderYOYO; København; On-site; DKK 900,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Growth opportunities

Growing international company

Job summary

OrderYOYO seeks a Lead Data & AI Platform Engineer to own and modernise the data platform during a critical scaling phase. You will lead architecture across lakehouse, warehouse, notebooks, and pipelines, ensuring trusted metrics and AI-enabled reporting.

You will guide data engineers, BI analysts, and data scientists, champion governance, and deliver automated reporting with robust monitoring and runbooks. This role is based in Denmark and offers growth opportunities.

Qualifications

• Proven experience in modern data platform engineering or data architecture.
• Experience leading complex data-platform work in SaaS, marketplace, fintech, or multi-region settings.
• Strong Fabric, Azure Synapse, Databricks, or lakehouse expertise.
• Expert SQL/T-SQL and production-grade data pipelines in Python or PySpark.
• Strong Power BI and DAX with semantic modelling and governance.

Responsibilities

• Lead architecture and evolution of the data platform across lakehouse, warehouse, and pipelines.
• Make Fabric the trusted source of truth for business metrics and reporting.
• Drive migration from legacy systems to governed semantic models.
• Build production-grade data pipelines across APIs, files, events, CRM, payments, and acquired data.
• Apply AI/automation to accelerate ETL/ELT, data mapping, testing, and monitoring.
• Design reusable semantic models and govern metric definitions for leadership teams.

Skills

Data platform engineering

SQL/T-SQL

Python/PySpark

Power BI/DAX

Azure Databricks

Microsoft Fabric

Data governance

ETL/ELT

AI/Automation in data

Leadership

Tools

Azure Synapse

Delta Lake

Power BI

Job description

Lead Data & AI Platform Engineer

At OrderYOYO, data powers executive reporting, payments, finance, merchant insights, product analytics, AI, marketing automation, operational decision-making, and M&A integration.

We are looking for a Lead Data & AI Platform Engineer to own the next stage of our data platform evolution. This is a hands-on technical leadership role for a strong engineer who can build reliable data systems, modernise our data lake, automate data pipelines, and pioneer the practical use of AI across data engineering, reporting, analytics, and business insight generation.

Competitive salary, growing international company, and growth opportunities.

You will play a central role in making OrderYOYO a more data-driven and AI-enabled company.

Role mission

Your mission is to lead the continuity, modernisation, and AI-enablement of OrderYOYO’s data platform during a critical scaling phase.

Core responsibilities

• Lead the architecture and evolution of OrderYOYO’s Microsoft Fabric platform across lakehouse, warehouse, notebooks, pipelines, semantic models, Power BI, and governance.
• Make Fabric the trusted source of truth for priority business metrics and reporting.
• Drive migration from legacy reporting and fragmented metric tooling into governed semantic models.
• Build and improve production-grade data pipelines across APIs, files, events, CRM systems, payment platforms, operational databases, and acquired-company data sources.
• Use AI and automation to accelerate ETL/ELT development, data mapping, documentation, testing, report generation, monitoring, and data-quality management.
• Design reusable semantic models, DAX measures, and governed metric definitions for leadership, finance, commercial, product, marketing, payments, support, and operations.
• Build automated reporting and insight-generation capabilities that reduce manual analysis and improve decision speed.
• Establish robust orchestration, monitoring, alerting, lineage, data-quality checks, and incident-response processes.
• Support CRM and operational data integrations, including identity mapping, schema mapping, outbound data feeds, reverse-ETL patterns, and monitoring.
• Create repeatable ingestion and modelling patterns for acquired businesses, making future integrations faster, cleaner, and more auditable.
• Define engineering standards for data pipelines, notebooks, semantic models, documentation, code review, testing, release management, and runbooks.
• Lead and mentor data engineers, analytics engineers, BI analysts, data scientists, and ML/AI practitioners.
• Partner with business stakeholders to turn ambiguous questions into reliable metrics, trusted reports, and scalable data products.
• Ensure data and AI solutions are secure, privacy-conscious, auditable, and aligned with GDPR and internal governance requirements.

Must-have requirements

• Strong experience in modern data platform engineering, analytics engineering, data warehousing, or data architecture.
• Proven experience leading complex data-platform work in a SaaS, marketplace, fintech, payments, e-commerce, B2B2C, or multi-region business.
• Strong Microsoft Fabric capability, or deep Azure Synapse, Databricks, Delta Lake, or lakehouse experience with the ability to specialise quickly in Fabric.
• Expert SQL/T-SQL skills.
• Strong Python or PySpark engineering capability, with experience building maintainable, tested, production-grade data pipelines.
• Strong Power BI and DAX experience, including semantic modelling, incremental refresh, performance tuning, model governance, and capacity/cost awareness.
• Practical experience using AI or automation to improve data engineering, reporting, documentation, testing, monitoring, migration, or developer productivity.
• Experience building or operating production data systems with monitoring, alerting, incident triage, root-cause analysis, data-quality checks, lineage, and runbooks.
• Experience leading legacy-to-modern data platform migrations, including metric parity, stakeholder validation, change control, and safe decommissioning.
• Experience leading, mentoring, or technically guiding data engineers, analytics engineers, BI analysts, data scientists, or ML engineers.
• Strong judgement on when to move fast, when to standardise, when to automate, and when to say “not yet” with evidence.

Strong-to-have experience

• 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 merchant/customer intelligence tools.
• Experience with churn prediction, recommendations, personalisation, marketing automation, fraud/risk analytics, payments analytics, or finance automation.
• CRM-side data flows and reverse-ETL patterns, especially HubSpot, Salesforce, Zendesk, or similar platforms.
• M&A or acquired-company data integrations, including schema discovery, data profiling, file/API ingestion, master-data mapping, migration QA, and reporting continuity.
• GA4, BigQuery export, Google Ads, SEM feeds, Segment, or other event and marketing analytics sources.
• Responsible AI and governance experience, including RBAC, PII handling, audit logs, human approval flows, explainability, and GDPR-conscious design.