Senior Data Developer (Analytics Engineer), Brazil
Brazil
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: remote
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingTranslate business requirements into technical specifications for analytics and AI
Own data products from ingestion and modeling through validation and delivery
Build data transformation layers with consistent business rules
Implement validation processes, automated testing and quality checks
Prepare structured data and data dictionaries for AI platforms
From the employer’s posting
translates them into robust, scalable technical solutions
Take full responsibility for the data products you build
Design and implement data transformation layers that pre-aggregate business information, apply consistent business rules
Implement and maintain rigorous validation processes, automated testing, and quality checks
Collaborate with AI teams to specify and prepare structured data, data dictionaries, and models
What you’ll bring
All qualificationsCore experience
- Senior experience in data engineering or analytics engineering
- Advanced SQL and Python for analysis, transformation and validation
- Solid data modeling and data warehouse design experience
- Hands-on experience with BigQuery or another cloud data warehouse
- Advanced or fluent English for daily international stakeholder communication
Qualification wording
Proven experience in a Data Engineering or Analytics Engineering role at senior level
Advanced proficiency in SQL and Python for data analysis, transformation, and validation
Solid experience in data modeling and data warehouse design
Hands-on experience working with BigQuery (or other cloud-based data warehouse platform)
Advanced/fluent English (reading, writing, and conversation)
Tools in this posting
- Python
- SQL
- Airbyte
- BigQuery
- dbt
- Airflow
Source — Tool mentions in context
- AI Enablement & Data Structuring: Collaborate with AI teams to specify and prepare structured data, data dictionaries, and models that enable AI platforms and intelligent reporting capabilities. - Full-Stack Data Development: Build and maintain data ingestion pipelines from multiple sources, implement transformations in SQL and Python, and ensure performance and scalability of solutions. - Proactive Problem Solving: Go beyond fulfilling requirements — proactively identify improvement opportunities, anticipate internal customer needs, propose innovative solutions, and challenge approaches when necessary.
- Proven experience in a Data Engineering or Analytics Engineering role at senior level - Advanced proficiency in SQL and Python for data analysis, transformation, and validation - Solid experience in data modeling and data warehouse design
- Experience with dbt (data build tool) for transformation and orchestration of analytical pipelines - Familiarity with data ingestion tools such as Airbyte or Airflow - Knowledge of automated testing best practices and CI/CD for data pipelines
- Solid experience in data modeling and data warehouse design - Hands-on experience working with BigQuery (or other cloud-based data warehouse platform) - Demonstrated ability to understand complex business logic and validate results from a business perspective, not just technical
Nice to Have: - Experience with dbt (data build tool) for transformation and orchestration of analytical pipelines - Familiarity with data ingestion tools such as Airbyte or Airflow
Benefits in the posting
Full benefits wording- -Health and dental insurance
- -Meal and food allowance
- -Childcare assistance
- -Extended paternity leave
- -Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass;
- -Life insurance
- -Discount club
- -Pregnancy and responsible parenting course
- -Partnerships with online learning platforms
- -Language learning platform
- We have a dedicated Health and Well-being team, inclusion specialists, and affinity groups who will be with you at every stage. Count on us to make this journey side by side.
- Employment type
- Homeoffice
From the employer’s posting.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 114 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 7, 2026 · 114 days ago
- Recorded sightings
- 289
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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- Check the listed location, eligibility and core experience before starting.
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Job 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.
Senior Data Developer (Analytics Engineer)
We are seeking a highly motivated Senior Data Developer (Analytics Engineer) who serves as a bridge between business and technology — someone who not only masters the technical stack but also brings strategic vision, deep understanding of business logic, and a proactive approach to solution design.
This professional will own the complete lifecycle of data products — from ingestion and modeling through final delivery — ensuring that data is structured, validated, and ready for consumption in AI and analytics environments. We need someone who communicates confidently with business stakeholders (both technical and non-technical), deeply understands the requirements behind requests, and translates them into robust, scalable technical solutions.
Responsibilities:
-
Business Translation & Requirements Definition: Actively engage with business stakeholders to understand context, challenges, and underlying needs; translate complex requirements into clear, detailed technical specifications that enable effective use of AI and analytics platforms.
-
End-to-End Product Ownership: Take full responsibility for the data products you build — from ingestion through modeling, transformation, validation, to final delivery and ongoing monitoring.
-
Data Quality Assurance & Validation: Implement and maintain rigorous validation processes, automated testing, and quality checks; act as guardian of data accuracy and integrity, ensuring metrics and KPIs accurately reflect business reality.
-
Data Modeling & Transformation: Design and implement data transformation layers that pre-aggregate business information, apply consistent business rules, and deliver datasets ready for consumption in dashboards and AI applications.
-
AI Enablement & Data Structuring: Collaborate with AI teams to specify and prepare structured data, data dictionaries, and models that enable AI platforms and intelligent reporting capabilities.
-
Full-Stack Data Development: Build and maintain data ingestion pipelines from multiple sources, implement transformations in SQL and Python, and ensure performance and scalability of solutions.
-
Proactive Problem Solving: Go beyond fulfilling requirements — proactively identify improvement opportunities, anticipate internal customer needs, propose innovative solutions, and challenge approaches when necessary.
-
Agile & High-Quality Delivery: Deliver reliable data solutions with speed and precision, balancing the need for rapid iteration with the highest quality standards.
-
Stakeholder Communication: Articulate technical concepts clearly to non-technical audiences; facilitate alignments, present solution proposals, and document modeling and architecture decisions.
Requirements:
-
Proven experience in a Data Engineering or Analytics Engineering role at senior level
-
Advanced proficiency in SQL and Python for data analysis, transformation, and validation
-
Solid experience in data modeling and data warehouse design
-
Hands-on experience working with BigQuery (or other cloud-based data warehouse platform)
-
Demonstrated ability to understand complex business logic and validate results from a business perspective, not just technical
-
Strong sense of ownership and proactive mindset — a professional who proposes improvements, challenges requirements when necessary, and doesn't wait to be asked to act
-
Experience specifying and preparing data requirements for AI or machine learning applications
-
Advanced/fluent English (reading, writing, and conversation) — constant communication with international stakeholders is required
-
Track record of delivering high-impact projects quickly and with quality
Nice to Have:
-
Experience with dbt (data build tool) for transformation and orchestration of analytical pipelines
-
Familiarity with data ingestion tools such as Airbyte or Airflow
-
Knowledge of automated testing best practices and CI/CD for data pipelines
-
Prior experience in Supply Chain, Retail, or Consumer Goods industries
-
Experience in projects involving data preparation for consumption via generative AI or conversational analytics platforms
-
Experience building business-oriented analytical reports (web reporting, custom visualizations)
#LI-JP3
Employment type
Homeoffice
Source details
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- Pay
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- Location & working pattern
Brazil
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