Senior Data Engineer [CET time zone]

We are looking for a Senior Data Engineer to be the technical reference for our Databricks data platform. You will design and run reliable pipelines, automate delivery through DataOps and CI/CD, and establish the governance that keeps data secure, traceable and ready for AI models used by global clients.

This is a remote position, and we will consider candidates from Portugal and a limited set of EU countries.

Our Client is a global player in the field of operations, risk, and sustainability services and solutions for companies and industries across the world. As they provide both services and technology for their clients, the Senior Data Engineer we are looking for will support the delivery of value across client's operations and technology ecosystem.

In this position, you are hired by FCamara Europe, the European division of one of the largest and fast-growing tech and cognitive services group in Brazil, with +1500 specialists and engineers. From Portugal we deliver services to the EU, UK, US and MENA, bringing together multicultural, diverse and creative teams through projects, managed services, squads, and staff augmentation.

Responsibilities

Data engineering on Databricks

• Design, build and optimise batch and streaming pipelines on Databricks (PySpark, Spark SQL, Delta Lake, Delta Live Tables / Lakeflow).
• Evolve the Lakehouse architecture (bronze, silver and gold layers) to ingest operational, behavioural and HSE data from multiple clients and formats.
• Ensure performance and cost efficiency of clusters, jobs and SQL Warehouses.
• Deliver trusted datasets to data science, AI and product teams.

DataOps and CI/CD

• Implement CI/CD pipelines for data code using Databricks Asset Bundles, Git and Azure DevOps or GitHub Actions.
• Automate data testing (unit, integration and quality) and promotion across dev, staging and production.
• Provision infrastructure as code (Terraform) and standardise pipeline templates.
• Monitor pipelines, define SLAs and alerts, and lead incident reviews.

Governance and data quality

• Implement and administer Unity Catalog: catalogs, permissions, lineage and auditing.
• Define policies for security, access control, data masking and per-client data isolation.
• Ensure compliance with LGPD, GDPR and the contractual requirements of global clients.
• Establish metadata standards, data contracts and quality metrics.

Technical leadership

• Act as a technical reference, reviewing code and mentoring mid-level and junior engineers.
• Partner with product, data science and consultants to turn business needs into data solutions.
• Document architecture, standards and best practices.

Requirements

• 6+ years in data engineering, including 3+ years with Databricks in production.
• Strong Python, PySpark and advanced SQL.
• Solid experience with Delta Lake and Lakehouse (medallion) architecture.
• Practical DataOps experience: automated testing, observability and pipeline versioning.
• Data governance experience, ideally with Unity Catalog (access, lineage, auditing).

• Hands-on CI/CD for data (Git, Azure DevOps or GitHub Actions, Databricks Asset Bundles or similar).
• Cloud experience, ideally Azure (ADLS, Data Factory, Key Vault, Entra ID).
• Experience with agentic coding
• Infrastructure as code with Terraform.
• Fluent English to work with global teams and clients.
• Degree in Computer Science, Engineering, Information Systems or a related field.

Nice to have

• Databricks (Data Engineer Professional) or Azure (DP-203 / DP-700) certifications.
• Experience with multi-tenant SaaS platforms and per-client data isolation.
• MLOps knowledge (MLflow, Feature Store, Model Serving) and data pipelines for generative AI / RAG.
• Microsoft purview experience
• Data quality tools (Great Expectations, Lakehouse Monitoring, dbt).
• Streaming with Kafka, Event Hubs or Structured Streaming.
• Experience with HSE, industrial operations or risk management data.