Role: Data Engineer III
Division: Assessment & Qualifications Delivery
Location: Bangalore or Chennai, India
- About Pearson Qualifications: We are the UK's largest awarding body and we are regulated by Ofqual (England), CCEA Accreditation (Northern Ireland) and Qualifications Wales (Wales). We offer academic and vocational qualifications that are globally recognised and benchmarked, with educational excellence rooted in names like Edexcel and BTEC. In 2025, we issued 6.5 million grades to candidates worldwide.
About the role
The Data Engineer is responsible for developing and supporting data integration and transformation solutions across Pearson's enterprise data platforms.
Working within the Data Engineering team, you will develop Azure Data Factory (ADF) pipelines and SQL-based transformation logic to move data from operational systems into common data models used by downstream applications.
This is a hands-on engineering role and would suit someone with strong experience in both Azure Data Factory and SQL database development. You will work closely with Data Modellers, Architects and fellow Data Engineers to deliver reliable, scalable and maintainable data integration solutions.
About You
You are a hands-on Data Engineer with strong experience in Azure Data Factory and SQL database development. You enjoy solving complex data integration problems and are equally comfortable building cloud-based data pipelines and implementing SQL transformation logic within relational databases.
You have a strong engineering mindset, write clean, maintainable code and are comfortable working within an Agile delivery environment.
Key Responsibilities
- Design, develop and maintain reusable, parameterised Azure Data Factory (ADF) pipelines following established engineering standards.
- Develop SQL-based transformation logic to convert source data into target data models using complex queries, stored procedures, views and functions.
- Build and maintain database objects within Azure SQL Managed Instance, Aurora MySQL or PostgreSQL.
- Analyse SQL execution plans and implement query optimisation and indexing strategies to improve database performance.
- Develop automation scripts to support database deployment and operational activities.
- Support database schema changes through GitHub and CI/CD pipelines.
- Work with Data Modellers and Architects to implement agreed data models and transformation logic.
- Support the diagnosis and resolution of issues relating to data pipelines, data transformations and database performance.
- Participate in code reviews and contribute to engineering best practices.
- Produce technical documentation where required.
Essential Skills & Experience
- Strong hands-on experience developing Azure Data Factory (ADF) pipelines.
- Strong SQL development skills, including complex queries, stored procedures, views and functions.
- Experience developing large-scale SQL data transformation solutions.
- Experience analysing SQL execution plans and implementing query optimisation techniques.
- Experience implementing indexing strategies and database performance tuning.
- Strong hands-on database development experience with SQL Server/Azure SQL, PostgreSQL and/or MySQL, with the ability to apply SQL engineering and performance-tuning skills across different relational database platforms.
- Experience developing ETL/ELT solutions.
- Experience using GitHub or similar version control systems.
- Good analytical and problem-solving skills.
- Experience working in Agile delivery teams.
Desirable Skills & Experience
- Familiarity with DACPAC-based database deployment.
- Hands-on experience with Databricks (Python or Scala) or DBT.
- Experience working with Change Data Capture (CDC).
- Experience with AWS Database Migration Service (AWS DMS) or similar database migration technologies.
- Exposure to enterprise data integration or platform-based environments.
- Azure or AWS certification.
Job Location and Hours
The role is aligned to our Bangalore or Chennai offices in India, working a 45 hour week. All our roles are hybrid working; our current policy requires our team to work from their base office 3 times per week.
