Remote EPOS & Loyalty Data Engineer – 12-Month Contract

NES Fircroft; England; Remote; GBP 83,000 - 117,000; Full time

Job summary

NES Fircroft is seeking an EPOS/Loyalty Data Engineer for a 12-month contract, fully remote in the UK. The role focuses on building and maintaining data pipelines for loyalty, payments, and EPOS systems, with emphasis on SCI, WRE, and identity-matching workloads. Start ASAP and inside IR35.

You will implement pipelines, manage loads, and support production releases, with exposure to Power BI datasets. Strong SQL, Python/Spark and Databricks skills required; remote, 40 hours per week.

Qualifications

• Strong SQL, Python/Spark and Databricks pipeline engineering.
• Experience with large-scale transaction, payment, loyalty, EPOS/WRE and identity-matching.
• Historical/full/incremental loads, high-water marks and reconciliation.
• Git/Azure DevOps PRs, unit testing, CI/CD and production release support.
• Reporting/Power BI dataset exposure desirable.
• SFMC/CIS integration and multi-market SCI knowledge desirable.

Responsibilities

• Implement and maintain SCI base, fact and curated pipelines.
• Deliver Elavon/PAR/WRE/payment and loyalty matching.
• Support ICE-to-EV data engineering and dashboard datasets.
• Implement DO-site and market-specific logic.
• Investigate volume drops, match-rate changes and data completeness defects.
• Execute controlled reloads, production validation, DQ/freshness controls and BAU support.
• Prepare PRs, tests, technical designs, CAB/release evidence and stakeholder

Skills

SQL

Python/Spark

Databricks

CI/CD

Data reconciliation

Tools

Git/Azure DevOps

Power BI

SFMC

Job description

NES Fircroft is seeking an EPOS/Loyalty Data Engineer for a 12-month contract, fully remote in the UK. The role focuses on building and maintaining data pipelines for loyalty, payments, and EPOS systems, with emphasis on SCI, WRE, and identity-matching workloads. Start ASAP and inside IR35.

You will implement pipelines, manage loads, and support production releases, with exposure to Power BI datasets. Strong SQL, Python/Spark and Databricks skills required; remote, 40 hours per week.