Senior Analytics Engineer: Lakehouse Data Platform Lead

Irwin Mitchell; England; Hybrid; GBP 85,000 - 110,000; Full time

Benefits offered by this job

25 days holidays + 8 bank holidays

Generous and flexible pension schemes

Volunteering days

Westfield Health membership

Flexible by Choice hybrid working

Job summary

Irwin Mitchell is hiring a Senior Analytics Engineer to lead curated data modelling within our Lakehouse environment. You will translate complex business requirements into robust SQL and PySpark transformations, owning the data serving layer for analytics deliverables.

You’ll mentor analysts and engineers, define KPI semantics, and collaborate with Data Analysts, Architects, and business stakeholders to ensure data quality, governance, and performance across the platform.

Qualifications

• Significant experience as an Analytics Engineer in a modern data platform environment.
• Expert-level SQL and strong PySpark experience.
• Deep understanding of dimensional modelling and semantic layers.
• Experience with Databricks and Lakehouse architecture.
• Strong stakeholder management and ability to mentor others.

Responsibilities

• Lead design and delivery of analytics-ready dimensional and semantic models.
• Own KPI definitions, conformed dimensions, and semantic consistency.
• Build PySpark and SQL pipelines on Databricks; ensure data quality and performance.
• Lead design reviews and contribute to architectural decisions.
• Collaborate with Data Analysts, Architects, Engineers, and stakeholders.
• Provide technical leadership and mentorship to analysts and engineers.
• Contribute to governance, testing, and CI/CD standards.

Skills

SQL

PySpark

Dimensional modelling

Stakeholder management

Mentoring / Leadership

Tools

Databricks

Lakehouse

CI/CD

Job description

Irwin Mitchell is hiring a Senior Analytics Engineer to lead curated data modelling within our Lakehouse environment. You will translate complex business requirements into robust SQL and PySpark transformations, owning the data serving layer for analytics deliverables.

You’ll mentor analysts and engineers, define KPI semantics, and collaborate with Data Analysts, Architects, and business stakeholders to ensure data quality, governance, and performance across the platform.