SC-Cleared Data Engineer – Hybrid Data Pipelines & Cloud

Pearson Carter; Reading; Hybrid; GBP 60,000 - 80,000; Full time

Benefits offered by this job

Inside IR35

Hybrid work (Reading)

Cloud data technologies exposure

Job summary

Pearson Carter is recruiting a Data Engineer to join a public sector programme in Reading. The role is hybrid (3 days onsite, 2 days remote) with current SC Clearance or the ability to obtain it.

You will build and maintain data pipelines and ETL/ELT processes across multiple data sources to support BI, reporting and future AI features. The ideal candidate has up to 2 years in data engineering or similar, strong SQL and Python, and experience with cloud platforms and data governance.

Qualifications

• Current SC Clearance or previously held SC Clearance.
• 2 years or less experience in Data Engineering, Software Engineering, Analytics or similar role.
• Strong SQL and Python skills.
• Understanding of ETL/ELT processes and data integration.
• Knowledge of relational databases and data engineering principles.
• Experience with Git or other version control systems.
• Excellent analytical and problem-solving skills.

Responsibilities

• Develop, maintain and support enterprise data pipelines and integration solutions.
• Build and maintain ETL/ELT processes across multiple data sources.
• Support cloud-based data platforms and contribute to enterprise data capabilities.
• Assist with data modelling, schema design and dataset creation for reporting and analytics.
• Monitor pipeline performance, troubleshoot issues and improve data quality and reliability.
• Collaborate with Data Analysts, Software Engineers and stakeholders to understand data requirements.
• Support data governance, security and best practices across enterprise data platforms.

Skills

SQL

Python

Job description

Pearson Carter is recruiting a Data Engineer to join a public sector programme in Reading. The role is hybrid (3 days onsite, 2 days remote) with current SC Clearance or the ability to obtain it.

You will build and maintain data pipelines and ETL/ELT processes across multiple data sources to support BI, reporting and future AI features. The ideal candidate has up to 2 years in data engineering or similar, strong SQL and Python, and experience with cloud platforms and data governance.