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Experience: 6–12 years
Client Domain: Banking / Financial Services
Location: As per client requirement / Hybrid
About the Job You Are Considering
We are looking for an experienced Cloud Data Engineer with strong hands-on expertise in AWS, dbt, Snowflake, PySpark, SQL, and cloud-based data engineering. The candidate will be responsible for designing, developing, and maintaining scalable data pipelines and analytics solutions for a banking client.
The ideal candidate should have experience in building modern cloud data platforms, implementing ELT/ETL pipelines, transforming large volumes of data, and ensuring data quality, performance, security, and compliance in a regulated banking environment.
Hybrid Working
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:
- Design, develop, and maintain scalable data pipelines using AWS cloud services, Snowflake, dbt, and PySpark.
- Build ELT/ETL workflows for ingestion, transformation, validation, and data consumption.
- Develop and manage dbt models, macros, tests, snapshots, documentation, and lineage.
- Perform data transformation and processing using PySpark and SQL.
- Work with Snowflake for data warehousing, data modelling, performance tuning, and secure data sharing.
- Integrate data from multiple sources such as relational databases, APIs, flat files, S3, streaming platforms, and third-party systems.
- Build curated, trusted, and reporting-ready data layers for analytics and business reporting.
- Implement data quality checks, reconciliation rules, audit controls, and exception handling.
- Optimize Snowflake queries, warehouses, partitions/clustering, and cost usage.
- Optimize PySpark jobs for memory usage, shuffle, partitions, and execution time.
- Develop and maintain data pipelines on AWS using services such as S3, Glue, Lambda, Step Functions, EMR, Redshift, IAM, CloudWatch, and related AWS services.
- Implement CI/CD practices using Git, Jenkins, GitHub Actions, GitLab CI, or AWS DevOps tools.
- Collaborate with architects, business analysts, data engineers, QA teams, and client stakeholders.
- Ensure data security, access control, encryption, masking, and compliance with banking standards.
- Support production deployments, incident management, troubleshooting, and root-cause analysis.
- Create technical documentation, data mapping documents, and operational runbooks.
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Your Skills:
- Strong hands-on experience with AWS cloud platform.
- Strong experience with Snowflake data warehouse.
- Hands-on development experience with dbt.
- Strong programming experience in PySpark.
- Excellent SQL skills, including complex joins, CTEs, window functions, stored procedures, and performance tuning.
- Experience in building ETL/ELT data pipelines.
- Good understanding of cloud data lake and data warehouse architecture.
- Experience with AWS S3 for data storage and ingestion.
- Experience with AWS Glue / EMR / Lambda / Step Functions or equivalent AWS data services.
- Experience in data modelling concepts such as star schema, snowflake schema, dimensional modelling, and data vault.
- Experience with file formats such as Parquet, Avro, JSON, CSV, ORC.
- Experience in implementing data quality, validation, reconciliation, and audit checks.
- Experience with version control tools such as Git, GitHub, Bitbucket, or GitLab.
- Experience with CI/CD pipelines and deployment automation.
- Strong debugging, analytical, and problem-solving skills.
- Develop modular and reusable dbt models.
- Create staging, intermediate, and mart layers using dbt.
- Implement dbt tests for data quality and validation.
- Create dbt macros for reusable logic.
- Maintain dbt documentation and lineage.
- Manage dbt snapshots for slowly changing dimensions.
- Use dbt Cloud or dbt Core depending on project setup.
- Integrate dbt with CI/CD pipelines.
- Follow dbt best practices for naming conventions, folder structure, and model dependency management.
- Develop Spark jobs using PySpark for large-scale data processing.
- Perform transformations, aggregations, joins, deduplication, and enrichment.
- Optimize Spark jobs for performance and resource usage.
- Handle large volumes of structured and semi-structured data.
- Work with data formats such as Parquet, ORC, Avro, JSON, and CSV.
- Implement error handling, logging, and restartability in PySpark jobs.
- Process batch and near-real-time data workloads as required.
We are a Disability Confident Employer:
Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:
- Declare they have a disability, and
- Meet the minimum essential criteria for the role.
Please opt in during the application process.
Make It Real (what does it mean for you):
You’d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.
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To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.
You will be joining one of the World’s Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.
Why you should consider Capgemini:
Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you’ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini:
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com
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