Data Analyst – Mid-level

Gauge

Data Analyst generating strategic insights from Itaú's credit product data. Involves data analysis, building pipelines, and collaborating with product and technology teams.

Posted 6/23/2026full-timeSão Paulo • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSETLNumpyPandasPythonSQLTableau

About the role

Key responsibilities & impact

Analyze credit product data (origination, usage, delinquency, risk, profitability) and generate strategic business insights.
Build, maintain and evolve analytical data pipelines in an AWS environment (S3, Glue, Step Functions and Athena).
Develop and optimize SQL queries for large volumes of data, supporting layered modeling in raw, trusted and curated stages.
Ensure data quality, consistency and traceability by implementing validations and handling inconsistencies.
Document processes, transformations and metric definitions.
Work closely with product, technology and business teams, translating analytical requirements into scalable solutions.
Participate in discussions on data architecture and modeling and share knowledge with the team.

Requirements

What you’ll need

Advanced SQL: CTEs, window functions (ranking, rolling aggregations, lag/lead), subqueries, complex joins, query optimization and execution plan analysis.
AWS: hands-on experience with S3 (storage and partitioning), Glue (ETL and cataloging), Step Functions (orchestration) and Athena (analytical queries).
Data Modeling: dimensional modeling (star/snowflake), Data Warehouse, Data Lake, layered architecture (raw, trusted, curated) and partitioning.
Data Quality: validation, handling inconsistencies, integrity/completeness testing and documentation of quality rules.
Business Analysis: structuring product-oriented analyses, defining and calculating metrics, interpreting results and clearly communicating findings.
Minimum Experience: 3–4 years in data analysis or analytical data engineering.
Python: Pandas, NumPy, automation of analytical processes and AWS integration via boto3.
Data Visualization: creating dashboards and selecting appropriate visualizations for each analysis.
Amazon QuickSight: building dashboards, calculated metrics and self-service analyses.
Financial Products: experience with credit product data (cards, loans, financing), financial metrics (delinquency, risk, profitability) and industry regulation.
Complementary Tools: Git/GitHub, Jupyter Notebooks and BI tools (Tableau, Power BI, Looker).

Benefits

Comp & perks

Meal Allowance / Food Allowance
Health insurance
Dental insurance
Day Off
Gympass / Totalpass
Childcare allowance
Pet care assistance
Fuel allowance
Home office allowance
Education reimbursement
Free online health platform
E-learning – Stefanini Academy with a variety of courses
Mentoring – Mentoring platform (an opportunity to meet people, develop skills and share experiences)
Discounts at partner institutions for undergraduate, postgraduate, language courses and other training
Perks and discounts at leading establishments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLAWSData ModelingData QualityBusiness AnalysisPythonData VisualizationAmazon QuickSightETLDimensional Modeling

Soft Skills

Analytical SkillsCommunicationCollaborationDocumentationProblem Solving