Systems Data Analyst: Bridge Data to Engineering

Dunelm; United Kingdom; Hybrid; GBP 45,000 - 65,000; Full time

Job summary

Dunelm is seeking a Systems Data Analyst to bridge source systems and data engineering, translating business questions into precise data requirements. You will model data concepts, validate data with SQL, and collaborate with Data Product Managers, Data Management, and engineers to deliver high-quality data products.

In this hybrid role, you will refine requirements, document data structures, and ensure readiness for implementation while contributing to data governance and scalable analytics

Qualifications

• Strong analytical and system analysis skills.
• Experience producing data models (conceptual, logical, physical).
• Strong SQL skills for data validation.
• Exposure to Python.
• Experience with enterprise data platforms.
• Clear written and verbal communication.
• Ability to produce structured, reusable documentation.

Responsibilities

• Understand the data lifecycle and origin business processes; map as-is and to-be flows.
• Analyse source systems and integrations to understand datasets and behaviours.
• Perform end-to-end data flow analysis into the data platform.
• Identify data quality issues, ambiguities, and risks in source data.
• Refine and define requirements; ensure readiness standards.
• Translate business needs into system-level data requirements.
• Define and maintain source-to-target data mappings.
• Produce data models (conceptual/logical/physical) and documentation.

Skills

Data modeling

SQL for data validation

System analysis

Python exposure

Enterprise data platforms

Written & verbal communication

Documentation

Curious & collaborative mindset

Tools

ETL/ELT pipelines

ERP/CRM/SCM systems knowledge

Job description

Dunelm is seeking a Systems Data Analyst to bridge source systems and data engineering, translating business questions into precise data requirements. You will model data concepts, validate data with SQL, and collaborate with Data Product Managers, Data Management, and engineers to deliver high-quality data products.

In this hybrid role, you will refine requirements, document data structures, and ensure readiness for implementation while contributing to data governance and scalable analytics