Data Analyst II, Mid-Level

• Transform data into reliable, useful information through querying, analysis, modeling, and visualization
• Support decision-making, process improvement, and the advancement of Celk’s technology solutions
• Extract, process, and integrate data from the Data Lake, databases, internal systems, and other sources, ensuring consistency and reliability
• Develop SQL queries and ETL/ELT processes for data extraction, transformation, validation, and delivery
• Support the evolution of the Data Lake by structuring layers, integrating new sources, creating datasets, and keeping the catalog, metadata, data dictionary, and documentation up to date
• Analyze data to identify patterns, trends, and inconsistencies; investigate root causes and propose solutions
• Translate the needs of internal teams and clients into metrics, KPIs, and visualizations
• Develop and maintain reports, dashboards, KPIs, and data models
• Ensure data quality, integrity, and security by applying access controls, internal policies, and LGPD requirements
• Work with Development, DevOps, and DBA teams to investigate issues and enhance solutions
• Identify opportunities for automation, query optimization, and cost reduction

• Bachelor’s degree completed or in progress in Data Science, Information Systems, Computer Science, Engineering, Statistics, or a related field
• Intermediate to advanced SQL skills in relational databases
• Data extraction, processing, analysis, and validation
• Development of reports, KPIs, and data visualizations
• Data modeling and relationships between tables
• Experience with BI tools such as Power BI, Amazon QuickSight, Tableau, or Qlik
• Understanding of Data Lake concepts and the differences between a Data Lake, Data Warehouse, and Lakehouse
• Data organization into layers, such as the medallion architecture (bronze, silver, and gold) or raw, trusted, and refined layers
• Knowledge of analytical file formats such as Parquet, ORC, Avro, CSV, and JSON
• SQL querying of Data Lake data using Amazon Athena, Trino/Presto, or Spark SQL, as well as data partitioning
• Data quality, integrity, and consistency management
• Interpretation of business rules and documentation of analytical criteria and results
• Information security principles and personal data protection requirements under Brazil’s LGPD

• Medical insurance
• Dental insurance
• Life insurance
• Meal/Food voucher
• Birthday day off
• Wellhub (formerly Gympass)
• Work from home
• Monday to Friday, 8:00 a.m. to 5:00 p.m. (40 hours per week)