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CI&T

AI Data Engineer – Mid/Senior

CI&T

AI Data Engineer creating reliable data products incorporating AI for impactful business solutions. Join a team transforming the potential of AI at CI&T.

Posted 7/3/2026full-timeCampinas • 🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing transformations and analytical models using Azure Databricks, ADF, and Power BI, while ensuring data quality and governance. Proficient in the SDLC with a strong focus on AI-assisted development and orchestration of workflows.

Highest-signal resume keywords
Advanced SQLData ModelingDatabricksAI-Assisted DevelopmentVersioning / GitHub

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data WarehousingData LakehousePythonQuality GovernanceSpec-Driven DevelopmentBuilding AgentsIntegration via MCPCreation of Slash CommandsOrchestration of WorkflowsCritical Evaluation of AI Outputs
Tools & Technologies
Azure DatabricksADFPower BIGitCI/CD
Industry Keywords
Data QualityTestingData ObservabilityBusiness-Oriented Semantic ModelsCorporate Metrics

Tech Stack

Tools & technologies
AzurePythonSDLCSQL

About the role

Key responsibilities & impact
  • Develop transformations and analytical models in Azure Databricks, ADF, Fabric and Power BI.
  • Build and maintain analytical layers (Bronze, Silver, Gold) and business-oriented Semantic Models.
  • Translate business rules into scalable data models; define, document and standardize corporate metrics.
  • Ensure data quality, testing and data observability.
  • Support the creation of datasets for Analytics and Agents.
  • Operate the SDLC with AI: code generation, testing, refactoring and AI-assisted debugging.
  • Structure specifications that feed AI (spec-driven development) and maintain quality control over outputs.
  • Build and orchestrate agents (multi-step, tool usage, planning + execution) integrated with repositories, pipelines and APIs.
  • Promote best practices in modeling, governance and documentation.

Requirements

What you’ll need
  • Advanced SQL
  • Data modeling, Data Warehousing / Lakehouse
  • Databricks and Python
  • Best practices for quality, governance and documentation
  • Versioning / GitHub
  • Spec-driven development (specification as the primary input for AI)
  • Strong command of the SDLC (design → build → test → deploy → operate)
  • Advanced use of AI in development (codegen, testing, refactor, debugging)
  • Building agents (multi-step, tool usage, planning + execution)
  • Creation of reusable skills and capability composition
  • Integration via MCP (Model Context Protocol) or equivalent
  • Creation of slash commands / operational interfaces based on structured prompts
  • Orchestration of workflows (multi-agent or human + agent)
  • Integration with tools (Git, CI/CD, issue tracking, observability)
  • Critical evaluation of AI outputs (quality, security, consistency)

Benefits

Comp & perks
  • Health and dental insurance
  • Food and meal allowances
  • Childcare assistance
  • Extended parental leave
  • Partnerships with gyms and health & wellness professionals via Wellhub (Gympass) and TotalPass
  • Profit Sharing (PLR)
  • Life insurance
  • Continuous learning platform (CI&T University)
  • Discount club
  • Free online platform dedicated to promoting physical and mental health and well-being
  • Pregnancy and responsible parenthood course
  • Partnerships with online course platforms
  • Language learning platform
  • And many more