About the Position:
JM Data Talent is inviting applications from experienced Databricks engineers for a contract assignment based in Dublin. This role centres on building and maintaining data pipelines within the Azure Databricks environment, using PySpark and SQL to support medallion-architecture Lakehouse design. The successful candidate will work with Delta Lake, Azure Data Factory and Unity Catalog to deliver governed, performant datasets that support downstream analytics and reporting. This is a hybrid position with an indicative duration of six months, reflecting the scale of platform work typically associated with Databricks modernisation projects. Well-structured pipelines and sound data-quality controls directly influence how reliably an organisation can trust its data, and this role sits at the centre of that effort. We welcome registrations of interest from engineers with a strong CI/CD discipline and a track record of tuning Spark workloads for cost and performance, for this and related upcoming assignments.
Job Details:
Post Date: 05 August 2026
Employment Type: Contract
Experience: 6+ Years
Job Location: Dublin, Ireland
Work Arrangement: Hybrid
Indicative Contract Duration: 6 months
Opportunity Status: Register Your Interest
Key Responsibilities:
Design and build scalable ETL/ELT pipelines within Azure Databricks using PySpark and SQL.
Implement and maintain a medallion (bronze/silver/gold) architecture across Delta Lake datasets.
Configure and govern data assets in Unity Catalog, aligning access controls with business requirements.
Integrate Azure Data Factory and Azure Data Lake Storage into end-to-end pipeline workflows.
Optimise Spark job performance, cluster configuration and cost efficiency across workloads.
Establish data-quality checks and validation routines within pipeline processes.
Build and maintain CI/CD pipelines for reliable, repeatable deployments.
Collaborate with data architects and analytics teams to align pipeline outputs with reporting needs.
Troubleshoot pipeline failures, performance bottlenecks and data-quality issues.
Document pipeline design, data lineage and operational procedures for ongoing support.
Required Skills:
Proven experience as a Data Engineer working extensively with Azure Databricks.
Strong hands-on PySpark development skills.
Solid working knowledge of Python and SQL for data transformation.
Practical experience with Delta Lake and medallion-architecture patterns.
Experience with Azure Data Factory and Azure Data Lake Storage.
Familiarity with Unity Catalog or equivalent data-governance tooling.
Experience building and maintaining CI/CD pipelines for data-engineering workloads.
Understanding of data-quality frameworks and validation techniques.
Demonstrated ability to optimise Spark job and cluster performance.
Comfortable working within Agile delivery environments.
Strong communication skills for engaging technical and business stakeholders.
Equivalent professional experience is welcomed in place of formal certification.
Desirable Experience:
Microsoft Azure or Databricks certification.
Experience working within data-governance-sensitive industries.
Familiarity with Azure DevOps for pipeline orchestration and release management.
Exposure to streaming data-ingestion patterns within Databricks.
Application Note: Candidates with strong Azure Databricks experience are encouraged to register their interest in this Dublin-based contract role. Please include your current location, work authorisation, availability and preferred working arrangement when applying, and a member of the JM Data Talent team will follow up with next steps.
Post Date:
Job Type:
Hybrid
Experience:
Senior
Job Location:
Dublin, Ireland
A contract opportunity for a Senior Databricks Engineer to build and optimise Lakehouse pipelines on Azure Databricks. The role covers PySpark development, Unity Catalog governance and medallion-architecture design for organisations modernising their Azure-based data platforms.
