> Markdown version of [/jobs/ext/4596055-data-engineer](https://www.wearedevelopers.com/jobs/ext/4596055-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Capgemini - **Location:** Birmingham, UK (Remote available) - **Experience:** Expert - **Salary:** £59,849 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Database, Computer Programming, Databases, Data Validation, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Security, Data Warehousing, DevOps, Amazon DynamoDB, Apache Hadoop, Python (Programming Language), Machine Learning, Open Source Technology, Cloud Services, Azure Machine Learning, Azure Data Lake, SAS (Software), Scala (Programming Language), Google Cloud, Data Storage Technologies, Azure Data Factory, Snowflake, Apache Spark, AWS Lambda, SC Clearance, Build Management, Amazon Relational Database Service, Data Lakes, Pyspark, Semi-structured Data, AWS Glue, Data Analytics, AWS Data Analytics, Data Management, Cloudwatch, Data Pipelines, Amazon Elastic Mapreduce (EMR), Amazon Redshift, Databricks, Programming Languages - **Published:** November 6, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5955444977 ## About the Role * Minimum 10+ years of experience as a Data Engineer or similar role. * Proven expertise in the technologies below, and data pipeline development and strong understanding of data warehousing concepts and practices. * Excellent problem-solving and analytical skills and strong communication and teamwork skills. In addition to these core skills, you should have specialist experience in one or more of the following technologies Azure Databricks * Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. * Experience of Databricks ML and Azure ML to develop predictive models and drive business insights. * Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. * Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. * Azure Data Engineer Associate and Databricks Certified Data Engineer Professional AWS * Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. * Programming Skills: Strong experience with modern programming languages such as Python, Java, Scala & Pyspark. * Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop. * Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both structured and unstructured data sets Further Info Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance. To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements. ## Description The Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms. We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP along with various data platforms like Databricks, Snowflake, Quantexa, Palantir, SAS. The Role You Are Considering As a Data Engineer, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. What You Will Bring * Design and build high-performance data pipelines: to extract, transform, and load data into Cloud Data Lake Storage and other Cloud services. * Develop and maintain secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. * Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data * Warehouses, Data Lakes, and Lake Houses using Open Source and cloud tools. * Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leveraging ML to develop predictive models and drive business insights. * Monitor and optimize data pipelines and infrastructure: Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability. * Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations. * Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices with a focus on how AI can support you in your delivery work