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Software Engineer - Data - Data Mesh & Lakehouse

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Onsite

Software Engineer - Data - Data Mesh & Lakehouse

Lawrence Harvey

Software Engineer - Data - Data Mesh & Lakehouse

Skills

Google Cloud PlatformData EngineeringKafkaDatabricksGitLabKubernetesApache AirflowAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Barcelona, Spain

Work mode:

Onsite

Published on:

31 August 2026

What they need


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 global 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 BigQuery.
  • 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, BigQuery

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: GitLab, Azure DevOps, JFrog Artifactory

Quality & Security: SonarQube, 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.

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