Data Engineer

Y-Axis; Greater London; Hybrid; GBP 45,000 - 55,000; Full time

Job summary

Y-Axis is seeking a data engineer to design and build scalable ETL/ELT pipelines across operational, analytical, and AI data environments. You will work with SQL and Python to deliver production-ready data solutions powering analytics and ML initiatives.

Collaboration with data scientists, product teams, and engineers is essential as you contribute to CI/CD, deployment automation, data governance, and engineering standards while mentoring peers.

Qualifications

• 5+ years of experience in data engineering or similar roles.
• Proficient in SQL and Python for production data solutions.
• Experience designing scalable ETL/ELT pipelines across data environments.
• Familiar with CI/CD, deployment automation, and ML data integration.

Responsibilities

• Design and develop scalable ETL and ELT pipelines across operational, analytical, and AI data environments.
• Build robust SQL and Python-based data solutions for production use.
• Develop and enhance data models that support analytics, machine learning, and customer insight initiatives.
• Contribute to CI/CD processes, deployment automation, and version-controlled engineering practices.
• Collaborate with data scientists, product teams, and engineers to deliver reliable and scalable solutions.
• Implement monitoring, validation, data quality controls, and governance processes.
• Support the integration of machine learning outputs into production environments.
• Mentor colleagues and contribute to engineering standards, documentation, and best practice development

Skills

SQL

Python

ETL

Job description

Full Time

Start Date

Immediate

Expiry Date

20 Dec, 26

50000.0

Posted On

21 Sep, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Information Services

Description

Specifically, you can expect to be involved in the following:

• Design and develop scalable ETL and ELT pipelines across operational, analytical, and AI data environments.
• Build robust SQL and Python-based data solutions for production use.
• Develop and enhance data models that support analytics, machine learning, and customer insight initiatives.
• Contribute to CI/CD processes, deployment automation, and version-controlled engineering practices.
• Collaborate with data scientists, product teams, and engineers to deliver reliable and scalable solutions.
• Implement monitoring, validation, data quality controls, and governance processes.
• Support the integration of machine learning outputs into production environments.
• Mentor colleagues and contribute to engineering standards, documentation, and best practice development

Responsibilities

Specifically, you can expect to be involved in the following:

• Design and develop scalable ETL and ELT pipelines across operational, analytical, and AI data environments.
• Build robust SQL and Python-based data solutions for production use.
• Develop and enhance data models that support analytics, machine learning, and customer insight initiatives.
• Contribute to CI/CD processes, deployment automation, and version-controlled engineering practices.
• Collaborate with data scientists, product teams, and engineers to deliver reliable and scalable solutions.
• Implement monitoring, validation, data quality controls, and governance processes.
• Support the integration of machine learning outputs into production environments.
• Mentor colleagues and contribute to engineering standards, documentation, and best practice development