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# Data Engineer

- **Company:** Megger
- **Location:** UK (Remote available)
- **Contract:** Permanent contract
- **Skills:** SAP Cloud, Databases, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Structures, Python (Programming Language), Cloud Services, Standard Sql, SAP (Applications), SAP NetWeaver Business Warehouse, Systems Integration, Data Lineage, SAP S/4HANA, Data Pipelines
- **Published:** September 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=967ea02ce8f279b0

## About the Role

* Previous experience in a Data Engineering role, with strong SQL and data modelling skills.
 * Experience with ETL/ELT processes and relational and/or analytical databases.
 * Experience integrating multiple source systems and a strong understanding of data quality and governance.
 * Experience with SAP / SAP BDC, BW/4HANA, SAP Analytics Cloud, Python or cloud data platforms would be desirable.
 * Degree or equivalent experience in a relevant data or technology discipline, with relevant professional qualifications or certifications desirable.

## Description

In this role, you will be responsible for designing, developing and maintaining data structures, pipelines and processes that support the organisation's analytical and reporting requirements. Working closely with business stakeholders, Data Analysts and reporting specialists, you will integrate data from multiple sources and transform it into reliable, well-structured and reusable datasets., * Design and maintain scalable data structures and models to support analytical and reporting requirements.

 * Build automated data pipelines and processes to integrate data from multiple source systems and reduce manual data preparation.
 * Monitor data pipelines, identify and resolve data quality issues, and implement appropriate validation and reconciliation processes.
 * Work with Data Analysts and business stakeholders to translate reporting requirements into appropriate datasets and data structures.
 * Maintain documentation covering datasets, transformations and data lineage, while identifying opportunities to improve data processes, automation and efficiency.