Data Engineer

Remote - UKFull-TimeMiddle

Salary not disclosed

Apply NowOpens the employer's application page

Job Details

Experience: 3 to 5 years' professional experience
Required Skills: PythonSQLGitMicrosoft Power BISparkCI/CDData modelingDatabricks

3 to 5 years' professional experience building and operating production data pipelines (ETL/ELT) in a commercial setting.
Hands-on Databricks proficiency: Unity Catalog, Spark Declarative Pipelines and metric views.
Strong SQL and Python applied to data engineering work.
Experience with data transformation/orchestration tooling such as Spark Declarative Pipelines, dbt, or an equivalent.
Solid grounding in data modelling (dimensional/star-schema approaches).
Git-based version control and CI/CD practices applied to data pipelines.
Experience ingesting data from source systems such as CRM (Salesforce, HubSpot) and telemetry tools (UserPilot, Pendo, Amplitude, Mixpanel).
Ability to operate with limited hand-holding.
Clear written and verbal communication skills.
Experience with Power BI or equivalent BI tools.
Experience implementing data governance or metric catalogues.
Experience using AI coding assistants such as Cursor, Claude, or GitHub Copilot.

Take operational ownership of the usage and adoption pipelines and their alerting.
Reconcile figures derived from our product-usage tool.
Separate development and production environments and mature CI/CD so deployment is repeatable and rollback is reliable.
Build and maintain Bronze-to-Gold pipelines in Databricks, Unity Catalog metric views, and the permissions/row-level-security model behind them.
Extend automated data quality checks across the underlying gold-layer tables and validate outputs against existing Power BI reports.
Co-own the scoping of the next set of usage and adoption signals with Product and Post-Sales.
Handle the realities of business system data including schema drift, inconsistent field naming, soft deletes, and incremental loads.
Lead the consolidation of additional data sources including support tickets, audit logs, and CRM systems.
Establish documented pipelines, an access model for raw and transformed data, and a working intake process for cross-department data requests.
Act as a credible point of contact for the Databricks estate.

View Full Description & ApplyYou'll be redirected to the employer's site