Senior Data Solutions Analyst

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Engage in the analysis, definition, and execution of data solutions, taking responsibility for conceptual, logical, and physical data modeling while ensuring data quality and supporting the corporate data architecture.

• A senior professional with extensive experience in data modeling, SQL, and the development of ETL/ELT pipelines, adept at working from requirements gathering through to implementation and maintenance of robust solutions in analytical and corporate settings.

• Collect, analyze, and document business requirements concerning data;

• Define conceptual, logical, and physical data models for both analytical and operational settings;

• Create, maintain, and optimize data ingestion, transformation, and provisioning pipelines;

• Execute ETL/ELT processes to merge multiple data sources;

• Ensure data quality, consistency, governance, and traceability;

• Collaborate with architects, data scientists, data engineers, and business stakeholders;

• Prepare both technical and functional documentation for data flows;

• Monitor performance and advocate for continuous improvement in loading and transformation processes;

• Assist in defining standards, best practices, and the organization's data architecture.

⛳️ Requirements

• A minimum of 4 years of experience in systems analysis, data engineering, or related fields;

• Demonstrated experience in enterprise data modeling projects;

• Involvement in constructing and maintaining large-scale data pipelines;

• Familiarity with modern data environments (Data Warehouse, Data Lake, and Lakehouse);

• Strong understanding of conceptual, logical, and physical data modeling;

• Experience with dimensional modeling (Star Schema and Snowflake);

• Knowledge of modeling for Data Warehouse, Data Mart, and Data Lake;

• Advanced proficiency in SQL;

• Familiarity with SQL Server, Oracle, PostgreSQL, MySQL;

• Experience in developing ETL/ELT pipelines;

• Knowledge of batch and streaming data processing;

• Implementation experience of integrations between diverse data sources, APIs, and corporate systems;

• Handling, enrichment, and transformation of data quality;

• Familiarity with Git and version control practices;

• Proficiency in Python (preferred);

• Experience in Cloud environments (Azure, AWS, or Google Cloud Platform);

• Understanding of Data Lakehouse architecture;

• Concepts of Dimensional Modeling (Data Warehouse and Data Marts);

• Integration of analytical solutions and BI platforms.

🏝️ Benefits

• 100% remote.