Data Engineer: Python, PySpark & SQL (Hybrid)

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

Job summary

Capgemini is seeking an experienced Data Engineer in Northampton to design, develop and optimize scalable data pipelines using Python, PySpark and SQL. You will work across big data technologies, collaborate with stakeholders, and help modernize data platforms in a hybrid environment.

Ideal candidates will have 7–9 years in data engineering, strong Python and PySpark skills, expert SQL, and exposure to Scala and cloud platforms such as Azure, AWS, or GCP.

Qualifications

• Design, develop and maintain scalable data pipelines and ETL processes.
• Write complex and high-performing SQL queries for data extraction, transformation and analysis.
• Hands-on Python development and PySpark for large-scale data processing.
• Experience with distributed computing frameworks and big data technologies.
• Exposure to Scala and 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

Python

PySpark

SQL

Scala exposure

Cloud platforms

Tools

Azure

AWS

GCP

Job description

Capgemini is seeking an experienced Data Engineer in Northampton to design, develop and optimize scalable data pipelines using Python, PySpark and SQL. You will work across big data technologies, collaborate with stakeholders, and help modernize data platforms in a hybrid environment.

Ideal candidates will have 7–9 years in data engineering, strong Python and PySpark skills, expert SQL, and exposure to Scala and cloud platforms such as Azure, AWS, or GCP.