Data Engineer - Snowflake ,DBT

Capgemini Financial Services
London, UK
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Adaptable Database Systems Artificial Intelligence Airflow Data Analysis Cloud Computing Cluster Analysis Code Review Continuous Integration Information Engineering Data Transformation Data Warehousing Database Development
+11 more
Performance Tuning Query Optimization SQL Stored Procedures PL-SQL Workflow Management Systems Data Processing Snowflake Data Build Tool (dbt) Git Star Schema Software Version Control

Job description

Get the future you want! Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role Capgemini Financial Services is seeking a Data Engineer with deep expertise in DBT (Data Build Tool), Snowflake, and PL/SQL to join our growing data team. Person will be responsible for designing, developing, and maintaining robust data transformation pipelines that support business intelligence, analytics, and data science initiatives. Key Responsibilities: Design and implement scalable data models and transformation pipelines using DBT on Snowflake. Write efficient and maintainable PL/SQL code for complex data processing and transformation tasks.

Requirements

Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions. Optimize Snowflake performance through query tuning, clustering, and resource management. Ensure data quality, integrity, and governance through testing, documentation, and monitoring. Participate in code reviews, architecture discussions, and continuous improvement initiatives. Maintain and enhance CI/CD pipelines for DBT projects. Required Qualifications: 5+ years of experience in data engineering or a related field. Strong hands-on experience with DBT (modular SQL development, testing, documentation). Proficiency in Snowflake (data warehousing, performance tuning, security). Advanced knowledge of PL/SQL and experience with stored procedures, functions, and packages. Solid understanding of data modeling concepts (star/snowflake schemas, normalization). Experience with version control systems (e.g., Git) and CI/CD practices. Familiarity with orchestration tools (e.g., Airflow, dbt Cloud, Prefect) is a plus. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with If you are interested in this role and for immediate consideration, please can you send me your CV ASAP

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.apply4u.co.uk

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · WWC Europe 2026

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · WWC 2024

7:27 min

How Git architecture fundamentally exposes historical code secrets

Dwayne Mcdaniel · LIVE

Videos

See all

Related articles

See all