Data Engineer  •  Jakarta Smart City

Feb 2022 - Current

• Implemented real-time data processing solutions for timely decision-making and improved customer experience.
• Increased efficiency of data-driven decision making by creating user-friendly dashboards that enable quick access to key metrics.
• Enhanced data quality by performing thorough cleaning, validation, and transformation tasks.
• Designed scalable and maintainable data models to support business intelligence initiatives and reporting needs.
• Managed cloud-based infrastructure to ensure optimal performance, security, and cost-efficiency of the company's data platform.
• Evaluated various tools, technologies, and best practices for potential adoption in the company's data engineering processes.
• Migrated legacy systems to modern big-data technologies, improving performance and scalability while minimizing business disruption.
• Streamlined complex workflows by breaking them down into manageable components for easier implementation and maintenance.
• .Fine-tuned query performance and optimized database structures for faster, more accurate data retrieval and reporting.
• Automated routine tasks using Python scripts, increasing team productivity and reducing manual errors.
• Proactively identified opportunities for process improvements, addressing inefficiencies through innovative solutions and implementing best practices in the field of data engineering.
• Established robust monitoring processes to proactively detect system anomalies or performance bottlenecks before they impact users or critical operations.
• Led end-to-end implementation of multiple high-impact projects from requirements gathering through deployment and post-launch support stages.
• Optimized data processing by implementing efficient ETL pipelines and streamlining database design.
• Collaborated with data scientists to develop machine learning models by providing the necessary data infrastructure and preprocessing tools.
• Developed custom algorithms for advanced analytics, driving actionable insights from large datasets.
• Provided technical guidance and mentorship to junior team members, fostering a collaborative learning environment within the organization.
• Conducted extensive troubleshooting to identify root causes of issues and implement effective resolutions in a timely manner.
• Collaborated with cross-functional teams for seamless integration of data sources into the company''s data ecosystem.
• Generated detailed studies on potential third-party data handling solutions, verifying compliance with internal needs and stakeholder requirements.
• Designed compliance frameworks for multi-site data warehousing efforts to verify conformity with state and federal data security guidelines.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.
• Used GDP on validation protocols, test cases and changed control documents.
• Communicated new or updated data requirements to global team.
• Developed, implemented and maintained data analytics protocols, standards, and documentation.
• Contributed to internal activities for overall process improvements, efficiencies and innovation.
• Explained data results and discussed how best to use data to support project objectives.
• Analyzed complex data and identified anomalies, trends, and risks to provide useful insights to improve internal controls.
• Prepared written summaries to accompany results and maintain documentation.
• Designed advanced analytics ranging from descriptive to predictive models to machine learning techniques.
• Designed and developed analytical data structures.
• Built databases and table structures for web applications.
• Prepared documentation and analytic reports, delivering summarized results, analysis and conclusions to stakeholders.