Contract Data Engineer: ETL, SQL & Dashboards

The Trust; City Of London; On-site; GBP 60,000 - 90,000; Full time

Job summary

The Trust is seeking a temporary Data Engineer to design, build, and maintain scalable data pipelines, datasets, and reporting solutions to support cross-functional stakeholders. This role focuses on reliable metrics, dashboards, and insights across the business.

You will optimize SQL queries, develop data models, and ensure data quality while collaborating with product and analytics teams to translate requirements into robust data solutions.

Qualifications

• 4+ years as Data Engineer/BI Engineer/Analyst in a product- or service-based company.
• 2+ years of experience with SQL, ETL, and reporting (including production data pipelines).
• Experience in at least one programming language (Python or C++).
• Experience with structured datasets, data modeling concepts, and analytics/reporting workflows.
• Strong communication skills to document processes and explain technical concepts clearly.

Responsibilities

• Build, maintain, and optimize ETL/ELT data pipelines and data models to support reporting and analytics use cases
• Write, troubleshoot, and optimize SQL queries for data extraction, transformation, validation, and performance
• Develop and maintain reporting datasets and documentation to improve data reliability and usability
• Partner with internal stakeholders to understand requirements and translate them into well-defined data solutions
• Implement data quality checks and monitoring to ensure accuracy, completeness, and timeliness of data outputs
• Support ad hoc data analyses and investigate data issues as needed

Skills

SQL

Python

Data modeling

ETL/ELT

Communication

Job description

The Trust is seeking a temporary Data Engineer to design, build, and maintain scalable data pipelines, datasets, and reporting solutions to support cross-functional stakeholders. This role focuses on reliable metrics, dashboards, and insights across the business.

You will optimize SQL queries, develop data models, and ensure data quality while collaborating with product and analytics teams to translate requirements into robust data solutions.