About the position
Databricks Consultant – Build and Optimise Production Lakehouse Pipelines
We’re looking for a hands-on Databricks Consultant who designs, builds and optimises lakehouse data pipelines and solutions on the Databricks platform.
This is a role for someone who likes getting into the platform and making data pipelines reliable, fast and cost-efficient. You’ll work across ingestion, transformation and delivery of curated data products using PySpark, Spark SQL and Delta Lake, together with job orchestration, performance and cost tuning, data quality and platform governance.
What you’ll do:
· Design, build and maintain production data pipelines for ingestion, transformation and delivery of curated data.
· Develop and optimise PySpark and Spark SQL transformations, including incremental and batch processing patterns.
· Design and operate Delta Lake tables, including table layout, optimisation and file-size management.
· Contribute to platform performance and cost efficiency through job, compute and query tuning.
· Implement data quality checks, validation, testing and clear technical documentation.
· Build and maintain workflow orchestration, job scheduling, retries and alerting for production pipelines.
· Apply Unity Catalog for data cataloguing, permissions and lineage where in use.
· Follow version control and CI/CD practices for notebooks, packages, jobs and pipeline configuration.
· Tune Spark jobs for scale and cost, including partitioning, shuffles, caching and cluster configuration.
· Ingest and transform data from enterprise and SaaS sources into well-structured medallion (bronze, silver, gold) or equivalent layers.
· Troubleshoot failed jobs, slow queries and data defects, and implement lasting technical corrections.
· Package reusable pipeline components, parameters and configuration for consistent delivery.
· Document pipeline design, table contracts, refresh behaviour and operational steps.
RequirementsWhat we’re looking for:
· Minimum two years of hands-on, day-to-day Databricks experience.
· Strong proficiency in Python, PySpark and Spark SQL.
· Practical experience building and operationalising data pipelines on Databricks.
· Experience working with Delta Lake, including table design and routine optimisation.
· Solid grasp of data modelling and the ability to write efficient, well-structured SQL and Spark transformations.
· Experience with incremental processing, orchestration and production operationalisation of pipelines.
· Experience on at least one major cloud platform (Azure, AWS or GCP).
· Familiarity with Databricks compute, jobs, workflows and SQL warehouses, including performance and cost awareness.
· Experience with Git-based version control and CI/CD for data workloads.
· Working knowledge of data quality checks, testing, technical documentation and access control.
Desired Skills:
- Databricks
- PySpark
- AWS
- Azure
- CI/CD
Desired Qualification Level:
- Degree
About The Employer:
