DBT Analytics Engineer: Trusted Data & Metrics

DBT Analytics Engineer: Trusted Data & Metrics

Full-Time 50000 - 65000 £ / year (est.) No working from home possible
Ci&T

At a Glance

  • Tasks: Develop and maintain DBT models while ensuring data quality for financial services.
  • Company: CI&T, a forward-thinking company in the financial sector.
  • Benefits: Flexible contract, opportunity to work with analytics teams, and enhance your skills.
  • Other info: 6-month contract with potential for growth and collaboration.
  • Why this job: Join a dynamic project and make an impact in the financial services industry.
  • Qualifications: Strong SQL and Snowflake skills, plus experience in modern data stack environments.

The predicted salary is between 50000 - 65000 £ per year.

CI&T is seeking a contractor in the Greater London area for a 6-month project focused on the financial services sector. The role involves developing and maintaining DBT models, supporting cross-domain data products, and ensuring data quality through the implementation of various tests and validations.

The ideal candidate will have strong skills in SQL and Snowflake, along with hands-on experience in modern data stack environments. This position offers a unique opportunity to work closely with analytics teams to create trusted analytics-ready datasets.

DBT Analytics Engineer: Trusted Data & Metrics employer: Ci&T

CIá is an exceptional employer for AI Engineers, offering a dynamic work culture that fosters innovation and collaboration. Located in the UK, employees benefit from extensive professional growth opportunities, access to cutting-edge technology, and a commitment to transforming AI into tangible business solutions. Join us to be part of a forward-thinking team that values your contributions and supports your career development.

Ci&T

Contact Details:

Ci&T Recruitment Team

We think you need these skills to ace DBT Analytics Engineer: Trusted Data & Metrics

Python
Communication Skills
SQL
Problem-Solving Skills
Automation
Attention to Detail
Data Quality Assurance