Data Engineer (On-site, Full-Time) [AS023]

Responsibilities

- Take over the existing data warehouse from the current third-party data provider during the handover period and then run it in-house.

- Maintain and improve the pipelines moving ERP data into the data warehouse so that data lands reliably and on time.

- Write, maintain and extend data models across staging, business logic, marts and reporting tables that feed the reporting layer.

- Read and understand the existing codebase before building new models.

- Implement and monitor data quality tests, deploying only once tests pass.

- Use version control consistently with disciplined commits, clear messages and branching.

- Answer business questions using data and explain findings clearly to non-technical colleagues, including the CEO and directors.

- Co-own technical documentation, core business definitions and the report library.

- Cross-cover with the Data Analyst on reporting during holidays and absence.

- Pick up occasional wider IT tasks, with training provided.

- Work collaboratively with the Data Analyst and speak directly with data owners across the business.

- Manage your own workload and own outcomes.

- Maintain a detail-oriented approach to data accuracy, testing and documentation while understanding the end-to-end business processes behind the data and asking “why before how”.

- Work flexibly within firm guardrails, with version-control discipline and test-before-deploy practices being non-negotiable.

- Frame and answer business questions rather than simply executing tickets.

- Learn quickly during the handover while maintaining a thorough approach focused on pipeline reliability, data quality and business adoption of reports.

Requirements

- 5+ years of data engineering experience for the global Senior route.

- Advanced SQL skills, including joins, CTEs, window functions, aggregations and debugging complex queries, with 5+ years of experience for the global route.

- 3+ years of commercial, hands-on Google BigQuery experience for the global route, with production BigQuery experience required.

- 3+ years of production dbt experience for the global route, including staging layers, business logic models, marts and tests.

- 1+ year of experience with Git/GitHub, including regular commits, clear commit messages and branching. GitLab or Bitbucket are acceptable substitutes.

- 1+ year of experience with data warehouse concepts, including ELT, layered modelling and dimensional modelling.

- Ability to communicate effectively with non-technical stakeholders, including CEO and director-level stakeholders.

- Experience with data pipelines and managed connectors for ingesting ERP data into BigQuery. Relevant approaches include Fivetran, Airbyte, Stitch, Azure Data Factory or custom Python ingestion.

- Experience with data quality testing and safe deployment, ensuring tests pass before deployment. Relevant approaches include dbt tests, Great Expectations or CI checks.

- Full overlap with UK business hours, including the GMT/BST change.

Nice to Have

- Basic Power BI experience for reporting and cross-cover with the Data Analyst. Looker, Tableau or other BI tools are acceptable alternatives.

- Basic Python skills for simple scripts and automation.

- Basic experience with Oracle NetSuite ERP data; experience with other ERP data such as Dynamics, SAP or Sage may be considered.

- Awareness of and interest in AI and emerging technology.

- Experience owning a pipeline or set of models end to end.