Senior Data Developer

New
C
CI&TFinance data
Listing location: Brazil; Workplace type: Remote; Structured job location: BrazilFull-TimeSenior
Salary not disclosed
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Job Details

Languages
Fluent English (B2)
Experience
4+ years of hands-on data engineering experience
Required Skills
SQLGitSnowflakeCI/CD

Requirements

  • Have 4+ years of hands-on data engineering experience, including nontrivial SQL-based transformation work on a cloud data warehouse.
  • Have experience with Snowflake.
  • Have experience building dimensional or curated data models from normalized or application-native source structures.
  • Have experience implementing Type 2 Slowly Changing Dimensions, including effective dating, current-record flags, and history preservation.
  • Have experience implementing or working within a reconciliation or data-quality framework, including variance detection, exception handling, and tolerance management.
  • Be familiar with temporal data modeling, including period state management, late-arriving facts, and effective-dated dimension attributes.
  • Have a solid Git-based development workflow and CI/CD promotion experience across dev, test/UAT, and production.
  • Understand sensitive-data handling in a governed platform, including access tiers, classification, and security-aware engineering practices.
  • Be fluent in English at B2 level for daily collaboration with a distributed engineering team and US client stakeholders.
  • Experience with dbt or a similar versioned SQL transformation framework is a nice to have.
  • Experience with Power BI or another enterprise BI platform as a downstream consumer is a nice to have.
  • Experience with financial or GL data modeling, or mortgage, lending, or financial-services data engineering, is a nice to have.

Responsibilities

  • Build versioned SQL transformation logic across the warehouse's staging, conformed, and curated layers using incremental, declarative patterns.
  • Recompute application-layer business logic, such as account balances and other derived values, as tested, versioned transformations.
  • Flatten and conform key-value and dimension-set source structures into standard dimensional attributes for reporting.
  • Capture logic from spreadsheets and point-report formulas as reusable, versioned transformations in the curated layer.
  • Implement layered reconciliation and data-quality checks from replication integrity through report-level parity.
  • Support downstream consumers of approved curated objects, including the BI semantic model and other reporting tools.
  • Participate in code review, CI/CD promotion, and automated regression testing.
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