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.

This role combines deep hands-on data engineering with technical ownership of a critical data layer. The Senior Data Developer will own the relational and lakehouse data behind a higher-education platform's program, student and enrollment data. That data has to be correct, fast and well governed, so that analytics, CRM and partner-facing applications can trust it. Success depends on taking ambiguous data problems from analysis to production on your own, making sound performance and modeling trade-offs, and keeping a high quality bar across the team.

Responsibilities:

Database Development: Design, build and tune schemas, stored procedures, views, functions and indexes. Lead query-plan analysis and performance work.
Lakehouse Engineering: Build and maintain Databricks pipelines (PySpark / Spark SQL) and dbt models using Kimball dimensional modeling.
Dual-Layer Delivery: Support both the transactional SQL databases used by applications and the lakehouse models used for analytics.
Data Governance & Quality: Manage data access and lineage in Unity Catalog. Implement quality checks and source-to-target reconciliation, and protect sensitive personal data (masking, row-level access).
Engineering Practices: Version database changes in Git, deploy through CI/CD, and review peers' SQL.
Knowledge Transfer & Operations: Take over existing schemas and jobs from previous teams without disrupting production. Document data models and runbooks, and support incident resolution and root-cause analysis.
Collaboration: Work with the Data Architect on modeling standards, and with application developers on API and data contracts.
Mentorship: Mentor mid-level developers and explain technical trade-offs to client architects.
Nearshore Delivery: Work with North American stakeholders and teams in Brazil and Colombia, keeping strong overlap with US business hours.

Requirements:

Advanced/fluent English (C1 or above)
Expert SQL (T-SQL and/or ANSI), including stored procedures, window functions, CTEs, indexing and execution plans
Solid experience with relational databases (SQL Server / Azure SQL preferred, or PostgreSQL or similar)
Hands-on production experience with Databricks, PySpark, Delta Lake and dbt
Solid experience with dimensional modeling (Kimball) and data warehouse design
Experience with Git, CI/CD for database changes and Jira

Nice to have:

Unity Catalog administration
Databricks certification (Data Engineer Associate / Professional)
Experience with orchestration and ingestion tools (Databricks Workflows, Airflow, ADF, Fivetran)
Experience with data quality frameworks (Great Expectations, dbt tests)
Exposure to BI tools (Power BI or Tableau)
Experience with regulated data (education, healthcare or privacy regulations such as LGPD)
Familiarity with AI-assisted development and agentic coding

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