Senior Data Developer, Brazil
Brazil
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: Full Time
From the employer’s posting
What you’ll work on
Full postingBuild ingestion pipelines for Databricks using a medallion architecture (bronze, silver, and gold layers), leveraging Auto Loader and Delta Lake.
From the employer’s posting
Responsibilities: Build ingestion pipelines for Databricks using a medallion architecture (bronze, silver, and gold layers), leveraging Auto Loader and Delta Lake. - Implement "before-and-after" reconciliation pipelines, including record counts, field-by-field comparisons, key/table mapping between versions, and large-scale validation rule application. - Model the gold layer for reporting, covering approval/rejection rates, reasons for outcomes, and views segmented by cluster and object. - Expose results via an API for a web application (using Databricks SQL Warehouse with the Statement Execution API, or a custom-built service) and document the API contract. - Configure governance within Unity Catalog—including permissions, data lineage, and auditing—which are critical for client production data. - Orchestrate processes using Workflows/Jobs, incorporate data quality checks (such as DLT expectations or similar), and manage version control via Databricks Asset Bundles. Requirements:
What you’ll bring
All qualificationsCore experience
- Experience in data engineering, with at least 2 years specifically using Databricks (PySpark, Delta Lake, Unity Catalog, Workflows).
Qualification wording
Experience in data engineering, with at least 2 years specifically using Databricks (PySpark, Delta Lake, Unity Catalog, Workflows). - Advanced proficiency in SQL and Python. - Experience with data reconciliation or validation within migration projects. - Knowledge of SAP data structures. - Experience in developing reports based on system data.
Tools in this posting
- Python
- SQL
- Databricks
- Delta Lake
- SAP
- PySpark
Source — Tool mentions in context
Requirements: - Experience in data engineering, with at least 2 years specifically using Databricks (PySpark, Delta Lake, Unity Catalog, Workflows). - Advanced proficiency in SQL and Python. - Experience with data reconciliation or validation within migration projects. - Knowledge of SAP data structures. - Experience in developing reports based on system data. - Advanced English for conversation.
Responsibilities: - Build ingestion pipelines for Databricks using a medallion architecture (bronze, silver, and gold layers), leveraging Auto Loader and Delta Lake. - Implement "before-and-after" reconciliation pipelines, including record counts, field-by-field comparisons, key/table mapping between versions, and large-scale validation rule application. - Model the gold layer for reporting, covering approval/rejection rates, reasons for outcomes, and views segmented by cluster and object. - Expose results via an API for a web application (using Databricks SQL Warehouse with the Statement Execution API, or a custom-built service) and document the API contract. - Configure governance within Unity Catalog—including permissions, data lineage, and auditing—which are critical for client production data. - Orchestrate processes using Workflows/Jobs, incorporate data quality checks (such as DLT expectations or similar), and manage version control via Databricks Asset Bundles. Requirements:
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
- Full Time
From the employer’s posting.
Posting record
Report an errorActively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 22, 2026 · 6 days ago
- Recorded sightings
- 56
- 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.
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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.
Responsibilities:
- Build ingestion pipelines for Databricks using a medallion architecture (bronze, silver, and gold layers), leveraging Auto Loader and Delta Lake.
- Implement "before-and-after" reconciliation pipelines, including record counts, field-by-field comparisons, key/table mapping between versions, and large-scale validation rule application.
- Model the gold layer for reporting, covering approval/rejection rates, reasons for outcomes, and views segmented by cluster and object.
- Expose results via an API for a web application (using Databricks SQL Warehouse with the Statement Execution API, or a custom-built service) and document the API contract.
- Configure governance within Unity Catalog—including permissions, data lineage, and auditing—which are critical for client production data.
- Orchestrate processes using Workflows/Jobs, incorporate data quality checks (such as DLT expectations or similar), and manage version control via Databricks Asset Bundles.
Requirements:
- Experience in data engineering, with at least 2 years specifically using Databricks (PySpark, Delta Lake, Unity Catalog, Workflows).
- Advanced proficiency in SQL and Python.
- Experience with data reconciliation or validation within migration projects.
- Knowledge of SAP data structures.
- Experience in developing reports based on system data.
- Advanced English for conversation.
Employment type
Full Time
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Brazil
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- Work authorization
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