Databricks Engineer

Challenge yourself and us

At AdvanceWorks, we learn together, grow together, and have fun together. And we do all this while creating great software solutions for clients across many industries and geographies.

We are constantly challenging ourselves and each other to use the latest technologies and the best methodologies and make sure we walk the talk.

What will be your role

We are looking for a

Databricks Data Engineer to join our team in Lisbon

and contribute to the development and evolution of modern data ingestion and Change Data Capture (CDC) solutions for a global organization operating at scale.

In this role, you’ll work on a modern data architecture built around Databricks, Apache Spark, Delta Lake, Azure, and Kafka, helping evolve a flexible and scalable approach to data ingestion across multiple source systems.

You’ll have an active role in defining and evolving ingestion patterns, developing Databricks notebooks and processing frameworks, configuring pipelines, and ensuring the integrity, traceability, and scalability of data throughout the process.

The project is moving from a traditional CDC approach focused primarily on Mainframe environments towards a more flexible architecture capable of supporting multiple data sources and destinations. This creates an opportunity to work on a technically challenging environment where Big Data, Cloud, CDC, and modern data engineering practices come together.

Your responsibilities will include

Developing and maintaining Change Data Capture (CDC) applications and data ingestion processes in Databricks

Creating and maintaining Databricks notebooks for setup, configuration, and data processing

Developing and parametrizing batch processing pipelines using Apache Spark

Implementing CDC logic to correctly detect and process inserts, updates, and deletes

Ensuring the generation of complete data snapshots while maintaining historical changes and data traceability

Working with Delta Lake to support reliable, scalable, and performant data processing

Working with multiple data sources, including Azure File Share, DB2, SQL Server, and SingleStore

Integrating processed data with destinations such as SingleStore and Kafka Confluent

Working with Databricks Workflows and Azure services to orchestrate and operationalize data pipelines

Optimizing processing performance and ensuring that pipelines are scalable and resilient

Contributing to the definition and evolution of data ingestion architecture and processing frameworks

Collaborating with other Data Engineers and technical teams to integrate processed data with downstream microservices

Ensuring data integrity, consistency, and traceability throughout migration and processing flows

Applying best practices around ETL/ELT, data engineering, monitoring, error handling, and pipeline reliability

Contributing to continuous improvement initiatives across the data platform and its ingestion frameworks

What should you bring to the team

3+ years of experience in Data Engineering, Databricks, or related data-intensive roles

Solid hands-on experience with Databricks, including notebooks, clusters, jobs, and workflows

Strong knowledge of Apache Spark, including batch processing and distributed data transformations

Strong experience with Python and SQL

Hands-on experience with Delta Lake and modern lakehouse architectures

Practical understanding of Change Data Capture (CDC) concepts and implementation patterns

Experience developing and parametrizing data pipelines and processing frameworks

Experience working with cloud data platforms, particularly Microsoft Azure

Familiarity with Azure services such as Azure File Share and Data Lake

Experience integrating data pipelines with Kafka, ideally Kafka Confluent

Good understanding of data architecture and ETL/ELT best practices

Experience designing scalable and resilient data processing solutions

Strong problem-solving skills and ability to troubleshoot distributed data processing environments

Strong communication skills and ability to collaborate with different technical teams

Availability to work in a hybrid model, 3 days per week in Tagus Park

Fluent Portuguese and English, both written and spoken

Nice to have

Experience with SingleStore

Experience with SQL-based CDC implementations across different database technologies

Experience with file-based CDC or ingestion frameworks

Knowledge of microservices and event-driven architectures

Experience with MLOps or Data Engineering in cloud environments

Familiarity with AI/GenAI pipelines and data platforms supporting AI initiatives

Experience with streaming technologies and event-driven data architectures

Knowledge of performance optimization techniques for Spark and Databricks

Experience designing resilient and highly scalable data solutions

What is in it for you

An amazing informal culture of smart, hardworking, and friendly people who support and care about each other

A mentorship program from day one

Opportunity to work on an innovative project combining CDC, Big Data, Cloud, Databricks, and Kafka

The chance to contribute to the evolution of a modern and scalable data architecture

Formal training and certifications in data, cloud, and engineering excellence

Access to cutting-edge tools and technologies

A dynamic company where your ideas matter more than job titles

Flexibility with responsibility

A Rubber Duck to help you debug those tricky Spark transformations

Don’t hold off any longer and apply now!

If you have any questions, drop us a line at