Senior Data Engineer (Databricks / Azure)

Livensa Group; Madrid; On-site; EUR 60,000 - 90,000; Full time

Job summary

Livensa Group is seeking its first data engineer to build and run a lakehouse on Databricks, ingest data from core systems and model it into trusted metrics for the business.

You will own pipelines from Mews, HubSpot, Dynamics 365, and analytics, deliver KPI data to Power BI, and lead CI/CD for the data platform on Azure DevOps. The role combines hands-on engineering, platform operations, and potential ML work across pricing, occupancy forecasting and revenue analytics.

Qualifications

• 5+ years as a data engineer with production pipelines you own end to end
• Strong Python, PySpark and SQL
• Hands-on Databricks (or Spark on another lakehouse) and Azure data services
• CI/CD and infrastructure as code (Azure DevOps or GitHub Actions; Terraform or Bicep) for data workloads
• Data modelling for analytics (dimensional or similar) and data quality practices
• Integration with REST APIs and event streams (webhooks, Event Hubs, Service Bus or Kafka)
• Professional Spanish & English; you can agree a metric definition with finance and commercial teams

Responsibilities

• Build ingestion pipelines from core systems: Mews, HubSpot, Dynamics 365, web/app analytics
• Work on platform integrations with Mews and other systems (webhooks, sync and billing services)
• Model data in Databricks (Unity Catalog, Delta Lake, medallion architecture) with PySpark and SQL
• Deliver data behind KPIs (occupancy, revenue, rebooking, conversion) to Power BI and other systems
• Own CI/CD for the data platform in Azure DevOps with tests and data quality monitoring
• Provide deployments and cloud operations support for the whole platform and coach other engineers
• Contribute to analytical and ML work: forecasting, pricing, occupancy mix, language models

Skills

Python

PySpark

SQL

Databricks

Azure data services

CI/CD

Infrastructure as code

Data modelling

REST APIs

English & Spanish

Tools

Databricks

Azure DevOps

GitHub Actions

Terraform

Bicep

Job description

Livensa is one of Europe's leading student and flex living operators, with around 12,000 beds across Spain and Portugal and plans to grow into Italy, Germany, France and Austria. Part of the Nido Living group, owned by CPP Investments. After two portfolios merged and moved onto one new platform, we are building a single source of truth for occupancy, revenue and the resident journey, and the foundation for pricing and AI.

The role

You will be the first data engineer on the team, reporting to the Head of Data & AI. You will build and run our lakehouse on Databricks: ingest data from our operational systems, model it into metrics the business trusts, and put it into production with proper pipelines and monitoring.

What you will do

• Build ingestion pipelines from our core systems: Mews (PMS and billing), HubSpot (CRM), Dynamics 365, web and app analytics, and legacy sources being retired.
• Work on the platform's integrations with Mews and our other operational systems (webhooks, sync and billing services, Service Bus and Event Hubs), together with the product team.
• Model data in Databricks (Unity Catalog, Delta Lake, medallion architecture) with PySpark and SQL.
• Deliver the data behind company KPIs (occupancy, revenue, rebooking, conversion) and serve it to Power BI and other systems.
• Own CI/CD for the data platform in Azure DevOps (Databricks Asset Bundles, Terraform), with tests, data quality checks and monitoring.
• Act as the senior engineer on deployments and cloud operations for the whole platform, backing up and coaching the Full Stack engineer.
• Contribute to analytical and ML work as it starts: demand forecasting, pricing and occupancy mix, language models.

What you bring

• 5+ years as a data engineer, with production pipelines you've owned end to end.
• Strong Python, PySpark and SQL.
• Hands-on Databricks (or Spark on another lakehouse) and Azure data services.
• CI/CD and infrastructure as code (Azure DevOps or GitHub Actions; Terraform or Bicep), for data workloads and ideally for application deployments.
• Data modelling for analytics (dimensional or similar) and data quality practices.
• Integration with REST APIs and event streams (webhooks, Event Hubs, Service Bus or Kafka).
• Professional Spanish & English; you can agree a metric definition with finance and commercial teams.

Nice to have

• Data science or ML experience: forecasting, pricing or revenue management, MLflow.
• Power BI and semantic models; C# / .NET (our integration services are built in it).
• Build the data platform of a growing European operator, almost from scratch.
• Direct impact on pricing, occupancy and NOI decisions.
• Modern Azure + Databricks stack, managed services, and room to automate.