Senior Data Engineer - Python, PySpark & SQL (Hybrid)

Capgemini; Northampton; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Capgemini in Northampton is seeking an experienced Data Engineer to design, develop and optimize large-scale data pipelines using Python, PySpark and SQL. The role blends office, client site, and home-based work with a hybrid arrangement and opportunities to collaborate with cross-functional teams.

You will contribute to data platform modernization, work with cloud platforms, and help ensure data quality, performance, and scalability across enterprise environments.

Qualifications

• 7–9 years of experience in Data Engineering or related roles.
• Strong hands-on Python development experience.
• Proven PySpark experience for large-scale data processing.
• Strong SQL skills including optimization and performance tuning.
• Exposure to Scala is a plus.
• Experience with cloud-based or enterprise data platforms.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Develop and optimize data processing solutions using Python and PySpark.
• Write complex and high-performing SQL queries for data extraction, transformation, and analysis.
• Work with large datasets and distributed computing frameworks to support data engineering initiatives.
• Collaborate with architects, analysts, and business stakeholders to deliver data-driven solutions.
• Troubleshoot and resolve performance, scalability, and data quality issues.
• Contribute to data platform modernization and best practices.

Skills

Data engineering experience

Python development

PySpark

SQL (query optimization)

Scala exposure

Cloud platforms

Analytical and communication skills

Job description

Capgemini in Northampton is seeking an experienced Data Engineer to design, develop and optimize large-scale data pipelines using Python, PySpark and SQL. The role blends office, client site, and home-based work with a hybrid arrangement and opportunities to collaborate with cross-functional teams.

You will contribute to data platform modernization, work with cloud platforms, and help ensure data quality, performance, and scalability across enterprise environments.