28 days ago
Manchester, United Kingdom +3 moreSenior
Responsibilities
- Design and build scalable, high-performance data pipelines for extracting, transforming, and loading data into cloud data lakes and other cloud services.
- Develop and maintain secure data warehouses and data lakehouses, including data models, data quality checks, and governance practices.
- Implement ETL and ELT workflows connecting source systems to data warehouses, data lakes, and lakehouses.
- Build and deploy AI/ML models and integrate machine learning into data pipelines to support predictive modeling and business insights.
- Monitor and optimize data pipelines and infrastructure by analyzing performance metrics, identifying bottlenecks, and improving efficiency and scalability.
- Collaborate with business analysts, data scientists, DevOps engineers, and other cross-functional teams on data platform implementations.
- Continuously learn and apply evolving big data technologies, best practices, and AI-supported delivery approaches.
Requirements
- Minimum 10 years of experience as a Data Engineer or in a similar role.
- Proven expertise in data pipeline development and strong understanding of data warehousing concepts and practices.
- Strong problem-solving, analytical, communication, and teamwork skills.
- Specialist experience in one or more relevant technologies, including Azure Databricks, AWS data services, or related cloud data platforms.
- For Azure-focused work, experience with Databricks, Apache Spark, Azure Data Lake Storage, Azure Data Factory, Databricks ML, and Azure ML is preferred.
- For AWS-focused work, experience with AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR, Amazon Athena, Amazon DynamoDB, Amazon CloudWatch, Amazon SNS, AWS Step Functions, AWS Redshift, AWS RDS, Hadoop, and AWS S3 is preferred.
- Strong programming experience with Python, Java, Scala, and PySpark is preferred.
- Azure Data Engineer Associate and Databricks Certified Data Engineer Professional certifications are relevant preferred qualifications.
- Must be eligible to obtain UK Security Check (SC) clearance, including meeting the requirement to have resided continuously in the United Kingdom for the last five years.
Benefits
- Hybrid-first working across company offices, client sites, and home, with no expectation of working from home 100% of the time.
- Flexible working arrangements are available to all UK employees.
- Training and development opportunities include thinktanks, hackathons, access to 250,000 courses, and external certifications from AWS, Microsoft, Harvard Manage Mentor, and cybersecurity programs.
- Positive work-life balance and opportunities to explore, innovate, and progress.
Tech Stack
Amazon DynamoDBAmazon RedshiftApache HadoopApache SparkAWSAzureDatabricksGoogle Cloud PlatformJavaPythonSassScalaSnowflake
Categories
Data Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.