Lead Analytics Engineer (Databricks)

Careerwise
Charing Cross, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Charing Cross, United Kingdom

Tech stack

Artificial Intelligence
Business Analytics Applications
Data analysis
Azure
Continuous Integration
ETL
Data Warehousing
Cursor (Graphical User Interface Elements)
Python
Raw Data
SQL Databases
Spark
Pandas
Star Schema
Data Pipelines
Databricks

Job description

Lead Analytics Engineer is required by a global software company to join their AI and Data Team and to shape the analytics layer, turning raw data into actionable intelligence that drives executive decision-making.

You will be responsible for:

  • Developing and maintaining robust data pipelines and data models in Databricks.
  • Building and enhancing structured data models that turn raw data into reliable, easy-to-understand information for the business.
  • Transforming fabric workflows into scalable and reliable analytics solutions.
  • Acting as the strategic technical partner for data-driven decision-making, ensuring a single source of truth.
  • Troubleshooting, analysing, and optimizing ETL processes while proactively identifying and resolving potential issues.
  • Documenting workflows, models, and pipelines for team and stakeholder reference.

Required experience and skills:

  • Strong experience in Databricks, including Spark, Delta Live Tables, Unity Catalog, and Medallion Architecture.
  • SQL and Python skills, with experience using Pandas in Databricks notebooks.
  • Good understanding of data warehouse design: Star Schema, F+D modelling, SCD/CDC concepts.
  • Experience building data pipelines, data warehouses, and lakehouses for BI, reporting, and analytics.
  • Familiarity with CI/CD pipelines, Azure DevOps, and AI development tools (eg, Cursor).
  • Relevant Azure and Databricks certifications a plus.
  • Excellent analytical, conceptual, and communication skills.

Requirements

  • Strong experience in Databricks, including Spark, Delta Live Tables, Unity Catalog, and Medallion Architecture.
  • SQL and Python skills, with experience using Pandas in Databricks notebooks.
  • Good understanding of data warehouse design: Star Schema, F+D modelling, SCD/CDC concepts.
  • Experience building data pipelines, data warehouses, and lakehouses for BI, reporting, and analytics.
  • Familiarity with CI/CD pipelines, Azure DevOps, and AI development tools (eg, Cursor).
  • Relevant Azure and Databricks certifications a plus.
  • Excellent analytical, conceptual, and communication skills.

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