Hybrid Data Engineer: Build Scalable Pipelines for QiCore

Quantum; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Private Health Care

Hybrid Working (3 days in office)

Travel Insurance

Competitive Base Salary

Company Bonus Scheme

AI Subscription (Claude / ChatGPT /Gem

Job summary

Quantum in London is seeking a Data Engineer to build and run pipelines for QiCore, integrating acquired data and ensuring data reliability and governance across the data warehouse. The role emphasizes production SQL and Python, collaboration with a fast-paced team, and driving data quality in a hybrid work setting.

You will contribute to analytics, reporting, and platform migrations while maintaining reporting continuity and scale for the business.

Qualifications

• Several years of hands-on data engineering with production SQL and Python.
• Experience building ETL/ELT pipelines on modern cloud warehouses.
• Knowledge of data governance, testing, and data quality practices.
• Familiar with orchestration, version control, and peer review.
• High quality standards with a can-do attitude.
• Strong teamwork and collaboration skills.
• Fluent English written and verbal.
• No ego and openness to feedback.

Responsibilities

• Build, test and maintain batch and streaming pipelines into QiCore to agreed engineering standards.
• Migrate Rewards data into our warehouse and single customer view, keeping reporting running throughout.
• Model data for analytics and reporting, following architecture and governance principles.
• Monitor pipeline health and data quality, fix root causes rather than patching symptoms.
• Support future acquisitions and platform migrations, turning each one into a faster, repeatable process.

Skills

Data engineering

SQL

Python

ETL/ELT

Cloud warehouse

Data governance

Data quality

Orchestration

Version control

Team player

Job description

Quantum in London is seeking a Data Engineer to build and run pipelines for QiCore, integrating acquired data and ensuring data reliability and governance across the data warehouse. The role emphasizes production SQL and Python, collaboration with a fast-paced team, and driving data quality in a hybrid work setting.

You will contribute to analytics, reporting, and platform migrations while maintaining reporting continuity and scale for the business.