Software Engineer
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- 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. xqbhyrx
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 (España)
🏢 Lawrence Harvey
📍 España