Analytics Engineer

Harnham; City Of London; On-site; GBP 36,000 - 60,000; Full time

Job summary

Harnham in London is seeking an Analytics Engineer to own data pipelines and lakehouse evolution, shaping modelling standards and best practices across Databricks, Azure Data Factory and Power BI.

You will translate business needs into scalable data models, build robust transformations, and collaborate with stakeholders to drive reliable reporting and analytics.

Qualifications

• Strong commercial experience with SQL.
• Experience in MS Azure environment.
• Hands-on Databricks.
• Expert understanding of data modelling principles.
• Experience with Azure Data Factory or similar orchestration tools.
• Ability to translate business needs into logical, scalable data models.
• Familiarity with Power BI semantic models or Tabular Editor.

Responsibilities

• Develop and maintain data pipelines across Databricks, Azure Data Factory and API-based integrations.
• Work across transformation layers in Databricks, ensuring clean, well-modelled datasets.
• Build and extend the Power BI data model, enabling reliable reporting and analytics.
• Partner with stakeholders to understand requirements, validate assumptions and shape data modelling.
• Apply strong data modelling practices, including star schemas and Kimball methodologies.
• Support lakehouse management, including incremental loads and data quality.
• Contribute to Databricks relationship to expand feature adoption.
• Organise and maintain the platform for stability and clarity across data sources.

Skills

SQL

Databricks

Power BI

Data Modelling

Azure Data Factory

Tools

Databricks

Azure Data Factory

Power BI

Job description

Analytics Engineer

London

Up to £60,000

This is a great opportunity to become the key Analytics Engineer within an early-stage data function, playing a defining role in how the organisation builds its lakehouse, models its core data, and shapes best practice for years to come. If you enjoy ownership, influence, and hands-on technical work across Databricks, data modelling, and pipeline development, this role offers genuine impact and long-term career growth.

The Company

They are investing heavily in their data capabilities and are building out a modern data stack to support smarter decision making across the business. The data team is still in its early stages, giving you the chance to help shape standards, strengthen their Databricks environment, and unlock more value from their growing data estate. Collaboration is central to how they work, with strong relationships across Technology, Finance, Operations and other key teams.

The Role

• Develop and maintain data pipelines across Databricks, Azure Data Factory and API-based integrations.
• Work across transformation layers in Databricks, ensuring clean, well-modelled datasets.
• Build and extend the Power BI data model, enabling reliable reporting and analytics.
• Partner with stakeholders to understand requirements, validate assumptions and shape how data should be modelled.
• Apply strong data modelling practices, including star schemas and Kimball methodologies.
• Support the management of the lakehouse, including incremental loads, snapshotting and data quality.
• Contribute to the relationship with Databricks to help expand adoption of its features.
• Organise and maintain the existing platform, ensuring stability and clarity across data sources.

Your Skills and Experience

• Strong commercial experience with SQL.
• Experienec working in MS Azure environment.
• Hands-on experience working with Databricks, or a strong desire to deepen expertise in it.
• Expert understanding of data modelling principles and semantic layer concepts.
• Experience working with Azure Data Factory or similar orchestration tools.
• Ability to translate business needs into logical, scalable data models.
• Comfortable working across multiple data sources and handling pipeline design.
• Experience with Power BI, including semantic models or Tabular Editor.
• Curious, collaborative mindset with the ability to push back constructively and guide stakeholders.