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 (Barcelona)
🏢 Lawrence Harvey
📍 Barcelona