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Brasil
Remote only
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.
About Us:
At CI&T, our rapid growth is fueled by the innovative solutions we create for our global clients. We are seeking Senior Data Engineers to build the curated data layer and reconciliation logic for a large-scale Finance data platform modernization at a major US mortgage lender — turning raw replicated data into governed, business-defined Finance measures. Two openings on this squad.
Responsibilities:
• Build transformation logic across the warehouse's staging, conformed, and curated layers in versioned SQL, using incremental, declarative transformation patterns.
• Recompute application-layer business logic — such as account balances and other derived values not present in raw replicated data — as tested, versioned transformation logic.
• Flatten and conform key-value/dimension-set source structures into standard dimensional attributes for reporting.
• Capture logic currently scattered across spreadsheets and point-report formulas as reusable, versioned transformation logic inside the curated layer.
• Implement layered reconciliation and data-quality checks, from replication integrity through report-level parity.
• Support enablement of downstream consumers (the BI semantic model and other reporting tools) against approved curated objects — never against raw source tables.
• Participate in code review, CI/CD promotion, and automated regression testing as part of an engineered data SDLC.
Requirements:
• Solid hands-on data engineering experience, including nontrivial SQL-based transformation work on a cloud data warehouse (Snowflake strongly preferred).
• Experience building dimensional/curated data models from normalized or application-native source structures.
• Experience implementing or working within a reconciliation/data-quality framework (variance detection, exception handling).
• Solid Git-based development workflow and CI/CD promotion experience (dev → test/UAT → production).
• Fluent English (B2) — daily collaboration with a distributed engineering team and client stakeholders.
Nice to Have:
• Experience with Microsoft Fabric, Power BI, or another enterprise BI platform as a downstream consumer.
• Experience with financial/GL data modeling (ledger entries, chart of accounts, dimension sets).
• Experience in mortgage, lending, or financial-services data engineering.
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