Description: * Ability to estimate timelines and support planning development, bringing technical insight to task sizing; * Skill to translate business requirements into efficient data models aligned with strategic objectives. * Experience with relational (SQL) and non-relational/columnar databases; * Proficiency in languages such as Python, Java, or Scala for distributed processing; * Knowledge of data modeling (Star Schema); * Experience with ETL processes and job orchestration in Databricks; * Hands-on experience in data processing and integration (APIs, databases, files, cloud storages), using tools such as pandas, PySpark, SparkR, or PL/SQL; * Experience in Data Lake projects; * Develop and maintain robust, scalable data pipelines (ETL), following best practices in data engineering and modeling; * Build and sustain databases to meet business objectives and regulatory requirements; * Create and maintain continuous data quality monitoring processes, implementing automated validations and alerting systems to identify and notify inconsistencies, anomalies, or pipeline failures; * Lead legacy data migration to Databricks, ensuring integrity, performance, and governance; * Collaborate with analysts and partner teams to ensure understanding of business rules and data consistency. * Support the evolution of data architecture by evaluating and implementing new tools and processes; 2512210202551931486