Sr. Data Administrator

When you think about a career, what comes to mind? Purpose? Collaboration? Being a protagonist to make a difference? At PagBank, we have all of that and much more. 💛 We are looking for people who wear the shirt with pride. People with the desire to make people's financial lives easier and drive businesses! Looking for a career that yields more? Check out this opportunity and #VemProPags!

Responsibilities and assignments

• Build, evaluate, and execute data update scripts with a focus on performance and security.
• Support analysis, diagnosis, and resolution of problems in development and production databases.
• Ensure best practices for relational and non-relational data modeling and persistence.
• Apply business rules and governance principles for information consistency and quality.
• Create data solutions in partnership with internal teams and related areas.
• Catalog data products and services to improve traceability and information use.
• Ensure data integration for information cross-referencing and metric tracking.
• Ensure the application of security policies in the data access layer.
• Foster automation of provisioning, configuration, and monitoring of database environments.

Requirements and qualifications

• Completed Higher Education in Information Technology, Computer Engineering, Computer Science, or related areas.
• Experience with high-criticality environments.
• Knowledge of SQL and PL/SQL.
• Knowledge of relational and non-relational data modeling.
• Experience with Oracle database.
• Knowledge of query tuning.
• Experience with DevOps culture.
• Knowledge of data purging.
• Intermediate English.

Additional information

• Experience with PostgreSQL.
• Experience with NoSQL databases, including Cassandra and MongoDB.
• Experience with ETL tools and data integration.
• Experience with heterogeneous databases in large-scale corporate environments.
• Experience with standardization and data catalog initiatives.
• Working in environments with high requirements for availability and control.
• Knowledge of data lifecycle management, real-time replication, and data masking.
• Knowledge of distributed systems and web applications.

Technological Environment:

• Database: Oracle, PostgreSQL, Cassandra, MongoDB.
• Languages and queries: SQL, PL/SQL.
• Data integration: ETL tools and integration pipelines.
• Data engineering: relational and non-relational modeling, information governance, purging.
• Operation and culture: DevOps, provisioning, configuration, and monitoring automation.