Senior Data Engineer: Build Scalable Pipelines & Databricks

Jobtailor; Birmingham; On-site; GBP 55,000 - 90,000; Full time

Job summary

Jobtailor in the United Kingdom is seeking a data engineer to build and maintain reliable, scalable data pipelines that support analytics, reporting, and data science.

You will collaborate with analysts and business teams to capture data requirements, optimise our Databricks platform, and implement ETL/ELT across multiple systems.

The role focuses on data quality, governance, and clear documentation, with hands-on work in Python, SQL, and Azure.

Qualifications

• Hands-on experience with cloud platforms (Azure preferred).
• Proven experience in Python and SQL.
• Experience building and optimise data pipelines and large-scale data processing systems.
• Good understanding of data modelling and data warehouse design.
• Experience with Databricks or similar modern data platforms.

Responsibilities

• Build and maintain reliable, scalable data pipelines to support digital enablement, reporting, analytics, and data science.
• Work closely with analysts, data scientists, and business teams to understand data requirements.
• Support and optimise our Databricks platform, ensuring it is used efficiently and at scale.
• Develop and maintain ETL/ELT processes to integrate data from multiple systems.
• Identify and fix performance issues in data pipelines and queries.
• Ensure data quality, security, and governance standards are met.
• Create clear documentation for data pipelines and platform design.

Skills

Data Pipeline Development

Python Programming

SQL Proficiency

Databricks Optimization

Cloud Platform Experience

Tools

Databricks

Azure

Job description

Jobtailor in the United Kingdom is seeking a data engineer to build and maintain reliable, scalable data pipelines that support analytics, reporting, and data science.

You will collaborate with analysts and business teams to capture data requirements, optimise our Databricks platform, and implement ETL/ELT across multiple systems.

The role focuses on data quality, governance, and clear documentation, with hands-on work in Python, SQL, and Azure.