Databricks Data Engineer — Remote Lakehouse Transformation

TechShack; España; Remote; EUR 78,000 - 106,000; Full time

Job summary

TechShack is seeking an experienced Databricks Data Engineer for a 12+ month remote contract. The role focuses on migrating legacy workloads to a modern Lakehouse on Databricks, designing scalable data pipelines and establishing engineering standards across the platform.

You will collaborate with architects, analysts and insurance stakeholders, delivering production-grade PySpark and SQL solutions while enabling downstream BI, analytics and future AI/ML use cases.

Qualifications

• 5+ years of data engineering experience.
• 2+ years of hands-on Databricks delivery in production.
• Proficient in Python (focus on PySpark) and SQL.
• Experience with data modelling (dimensional/Data Vault).
• Cloud experience, ideally Azure (AWS also considered).
• CI/CD and IaC practices for data platforms.

Responsibilities

• Design, build and maintain scalable batch and streaming pipelines on Databricks using PySpark and Delta Lake.
• Migrate legacy ETL/ELT workloads to the Lakehouse architecture.
• Implement Medallion patterns and reusable ingestion/transformation frameworks.
• Orchestrate workflows with Databricks Workflows, Delta Live Tables, Azure Data Factory or Airflow.
• Contribute to CI/CD and infrastructure as code using Databricks Asset Bundles, Terraform, Azure DevOps or GitHub Actions.

Skills

5+ years data engineering

2+ years Databricks delivery

Advanced Python

Advanced PySpark

Advanced SQL

Data modelling

Communication

CI/CD for data engineering

Tools

Databricks

Azure Data Factory

GitHub Actions

Terraform

Delta Lake

Airflow

dbt

Job description

TechShack is seeking an experienced Databricks Data Engineer for a 12+ month remote contract. The role focuses on migrating legacy workloads to a modern Lakehouse on Databricks, designing scalable data pipelines and establishing engineering standards across the platform.

You will collaborate with architects, analysts and insurance stakeholders, delivering production-grade PySpark and SQL solutions while enabling downstream BI, analytics and future AI/ML use cases.