- Location
- London
- Workplace
- Hybrid
- Type
- Contract
- Department
- Lovelace
- Seniority
- Mid
- Experience
- 30+ years
- Industry
- Technology
- Category
- Engineering
- Role type
- Individual Contributor
- Environment
- Office
- Source
- Lever
Overview
As a Data Analytics Engineer, you will build and maintain DBT models for cross-domain analytics use cases in the financial services sector. You'll create reusable facts, dimensions, and marts, implement data quality checks, and translate business requirements into trusted data models. The role involves working with analytics and domain teams to ensure datasets are fit for reporting and decision-making. Strong hands-on experience with DBT, SQL, and Snowflake is required, along with expertise in data modeling and metric design.
Description
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
Create reusable facts, dimensions and marts for analytics consumption
Support cross-domain data products such as Churn, LTV, Segmentation and Customer Intelligence
Implement dbt tests, source freshness checks and reconciliation logic
Translate business requirements into data models and metric logic
Support data quality checks and model validation
Document model definitions, business rules, assumptions and lineage
Work closely with analytics and domain teams to ensure datasets are fit for reporting and decisioning
We need someone with these skills:
Strong hands-on experience with DBT
Strong SQL and Snowflake experience
Experience building facts, dimensions, marts and analytics-ready data models
Strong understanding of data modelling and metric design
Experience implementing dbt tests, source freshness checks and data quality validations
Ability to translate business requirements into trusted data models
Experience working with analysts, product teams and business stakeholders
Good documentation skills for model logic, metric definitions and lineage
Experience working in modern data stack environments
Skills
Languages
Remote Scope
About CI&T
CI&T is a global digital specialist helping large enterprises transform AI potential into real business impact with 8,000 professionals across 25+ countries.