Software Engineer - Data | Data Mesh &

- Lakehouse About the Role We are looking for a Software Engineer - Data to join a central Data Delivery team building the foundation of a general Data Mesh platform based on a Lakehouse architecture . You will work on the engineering layer responsible for ingesting, processing and provisioning source-aligned data products into central data catalogs, enabling teams across the organisation to consume trusted data for analytics, reporting, machine learning and other data-driven applications. A key part of the platform is enabling scalable data consumption through zero-copy data sharing , while maintaining strong governance, security and data quality standards. What You'll Be Working On Design and build scalable batch and streaming data pipelines . Develop ingestion solutions for source-aligned data products. Work with Apache Spark and Databricks within a modern Lakehouse environment. Implement data ingestion strategies including Full Loads, Delta Loads and Change Data Capture (CDC) . Build and maintain streaming pipelines using technologies such as Kafka, Flink or Confluent . Manage datasets stored across Google Cloud Storage and Azure Blob Storage . Enable secure zero-copy data sharing through technologies such as Databricks Unity Catalog and Big Query. Implement data governance and access-control models including RBAC and attribute-based access control .



Design solutions capable of handling complex schema evolution , including backward and forward compatibility.

Tech Environment

Data &

- Processing: Apache Spark, Databricks, Big Query Streaming &
- Ingestion: Kafka, Flink, Confluent, Airbyte Cloud &
- Storage: GCP, Google Cloud Storage, Azure, Azure Blob Storage Orchestration &
- Platform: Airflow, Kubernetes Governance: Databricks Unity Catalog, RBAC, ABAC/CBAC, Data Contracts CI/CD: Git Lab, Azure Dev Ops, JFrog Artifactory Quality &
- Security: Sonar Qube, Snyk What We're Looking For Strong professional experience in Data Engineering or Software Engineering focused on data platforms . Hands-on experience with Databricks and Apache Spark .

Experience designing distributed data pipelines in cloud environments. Strong understanding of Lakehouse architectures .

Experience or strong knowledge of Data Mesh principles and Data Products .

Experience with batch and streaming ingestion patterns. Knowledge of CDC and incremental data processing strategies .

Experience dealing with schema evolution in production data pipelines. Understanding of modern data governance and access-control models .

Experience with Airflow, Kubernetes and CI/CD . Comfortable working collaboratively through code reviews and technical design discussions.

📌 Software engineer - data - data mesh & lakehouse (Madrid)
🏢 Lawrence Harvey
📍 Madrid