Team interview

As a Senior QA Data Engineer at Zallpy Digital, an official partner of BMW, he led and organized data quality initiatives focused on establishing quality frameworks, executing data validation strategies, and enhancing testing processes. His efforts directly contributed to ensuring the accuracy and reliability of data across ETL and reporting workflows supporting BMW projects.

His responsibilities included:

• Project Leadership: Directed dynamic data validation initiatives within ETL and reporting environments, ensuring data integrity throughout the entire lifecycle.
• Quality Frameworks: Designed and implemented structured quality frameworks to promote consistency, accuracy, and traceability across data operations.
• Test Planning and Execution: Created comprehensive test plans and executed systematic validation procedures to uphold high standards in data quality.
• Dynamic Data Validation: Developed adaptive validation strategies to handle varying data flow complexities and business rules.
• Technology Utilization: Applied ETL processes, data pipeline tools, and validation techniques to deliver reliable and scalable data quality solutions.

By applying these best practices and technologies, he helped maintain high standards of data reliability, directly supporting precise and trustworthy decision-making for BMW’s data-driven initiatives.

As a Senior Data Governance Engineer at 200DEV, he served as a third-party contractor for Cosan, where he led and organized projects centered on data privacy and compliance. His work focused on building and implementing key initiatives involving data inventory, data loss prevention, anonymization, and supplier risk management.

His responsibilities included:

• Project Leadership: Led and coordinated data governance initiatives to ensure compliance with industry regulations and reinforce data privacy practices.
• Data Inventory Processes: Developed and executed comprehensive data inventory procedures to support accurate data asset tracking and classification.
• Data Loss Prevention: Designed and implemented strategies to safeguard sensitive information and prevent data breaches.
• Data Anonymization: Applied anonymization techniques to protect personal and sensitive data, in line with privacy regulations.
• Supplier Risk Management: Assessed and mitigated supplier-related risks to ensure data protection across the supply chain.
• Technology Utilization: Employed Python, Azure, ETL frameworks, and data pipelines to deliver secure and scalable data solutions.
• Quality and Validation: Ensured data accuracy and integrity through rigorous quality assurance and validation protocols.

By leveraging modern technologies and governance best practices, he significantly strengthened Cosan’s data privacy framework, reduced operational risk, and contributed to more informed, secure, and compliant data management.

As a Senior Data Engineer at MazzaTech, he worked as a third-party contractor for Credit Suisse. He was responsible for leading projects focused on data governance, privacy, and protection. One of his key contributions was the development of a solution to identify toxic combinations of user access, improving the organization’s data security posture.

He primarily used Python and file manipulation techniques while creating profiling reports and visualizations to support compliance and decision-making. His responsibilities included:

• Data Governance Projects: Led initiatives aimed at ensuring data governance, privacy, and protection, in line with industry regulations and internal standards.
• Toxic Access Combination Analysis: Designed and implemented a system to analyze toxic user access combinations, strengthening system integrity and reducing risk.
• Technology Utilization: Applied Python to perform complex data manipulation, automate processes, and streamline workflows.
• File Manipulation: Managed large volumes of data files, executing efficient extraction, transformation, and loading (ETL) tasks.
• Profiling and Visualization: Produced comprehensive data profiling reports and developed visual dashboards to support strategic insights and compliance reviews.
• Collaboration and Compliance: Worked closely with cross-functional teams at Credit Suisse to ensure adherence to data protection regulations and deliver reliable data solutions.

By effectively applying these technologies and practices, he enhanced Credit Suisse’s data governance and security capabilities, providing impactful insights through structured analysis and automation.

As a Mid-Level Data Engineer at Flywheel, he was responsible for a broad range of ETL and data engineering activities. Assigned to a major client, Coca-Cola, he developed a data pipeline focused on ensuring data quality. He also contributed to projects involving image analysis and data collection volumetry.

He worked extensively with technologies such as AWS, PySpark, Redis, Python, Great Expectations, web scraping tools, and automation frameworks. His key responsibilities included:

• ETL Development: Designed and implemented ETL processes using PySpark and AWS to extract, transform, and load data from diverse sources into a data warehouse, ensuring data accuracy and consistency.
• Data Quality Pipeline: Developed and maintained a robust data quality pipeline for Coca-Cola, utilizing Great Expectations to uphold high standards of data integrity.
• Image Analysis Projects: Participated in initiatives involving advanced image analysis, applying data engineering techniques to manage and process large-scale image datasets.
• Data Collection Volumetry: Contributed to volumetric analysis projects aimed at optimizing data collection processes to improve accuracy and efficiency.
• Technology Utilization: Leveraged AWS, PySpark, Redis, and Python to build scalable, high-performance data solutions.
• Web Scraping and Automation: Implemented web scraping methods and automation tools to collect and process large volumes of data from various online sources.
• Collaboration and Innovation: Worked closely with cross-functional teams to deliver innovative data solutions addressing complex business problems.
• Through his consistent application of best practices and modern technologies, he played a significant role in improving data quality and operational efficiency, contributing to the success of data-driven projects for high-profile clients such as Coca-Cola.

As a Junior Software Developer specializing in legacy systems, he worked as a third-party contractor for Nestlé. He was responsible for ensuring and maintaining the integrity and performance of the system. His role involved writing and optimizing SQL procedures, creating and managing triggers, and maintaining the database management system (DBMS) to ensure smooth operations and data reliability.

During his tenure at Nestlé, he worked extensively with technologies such as SQL, Genexus, Python, and Windows Server. His main responsibilities included:

• SQL Development: He wrote and optimized complex SQL procedures to improve system functionality and performance.
• Database Management: He ensured the reliability and efficiency of the DBMS through routine maintenance and troubleshooting.
• Trigger Management: He created and managed database triggers to automate and enforce business rules within the system.
• System Maintenance: He utilized Genexus to develop and maintain key components of the legacy system, ensuring seamless integration and operation.
• Scripting and Automation: He used Python to automate processes and improve system efficiency, minimizing manual tasks.
• Server Management: He administered and maintained the Windows Server environment to support the legacy system’s infrastructure and operations.

By applying these technologies and methodologies consistently, he helped keep the legacy system robust, reliable, and aligned with Nestlé’s operational requirements. His work contributed to maintaining high standards of quality and performance, supporting the company’s long-term data strategy and operational success.

• Ticket management, issue resolution in databases and legacy systems
• Created reports, routine procedures, triggers to improve data management