Data Engineer with proven experience in designing and delivering scalable enterprise data solutions who is eager to take on greater responsibilities in project
and reporting transformation management. Skilled in building…
Data Engineer with proven experience in designing and delivering scalable enterprise data solutions who is eager to take on greater responsibilities in project
and reporting transformation management. Skilled in building reliable pipelines, microservices, and ETL processes that enhance reporting accuracy and support critical financial and operational priorities. Proven ability to maintain and enhance production systems, mentor teams, and contribute to continuous improvement
initiatives. Recognized for maintaining high standards of code quality, testability, and system performance, while also driving team alignment and smooth delivery.
Committed to growing into a leadership role, leveraging technical expertise to guide projects, optimize processes, and deliver measurable business impact..
Designed and developed ingestion pipelines to load 100M+ records into Enterprise Information Data (EID), improving data accessibility for business units and supporting strategic decision-making.
Built reusable ingestion templates, reducing development time for new sources and standardizing best practices across the team.
Acquired end-to-end experience in UIF and CAP frameworks, including DDL loading and fact table population, covering 10+ dimensions and facts.
Collaborated with stakeholders to support Enterprise Process Management (EPM) data platform initiatives.
Managed risks, issues, and dependencies, ensuring timely delivery of high-quality reporting solutions in EPM.
Captured lessons learned and implemented best practices to drive continuous improvement.
• Designed and developed ingestion pipelines to load 100M+ records into Enterprise Information Data (EID), improving data accessibility for business units and supporting strategic decision-making.• Built reusable ingestion templates, reducing development time for new sources and standardizing best practices across the team.• Acquired end-to-end experience in UIF and CAP frameworks, including DDL loading and fact table population, covering 10+ dimensions and facts.• Collaborated with stakeholders to support Enterprise Process Management (EPM) data platform initiatives• Managed risks, issues, and dependencies, ensuring timely delivery of high-quality reporting solutions in EPM.• Captured lessons learned and implemented best practices to drive continuous improvement.
• Developed and maintained 9+ microservices using Angular and Node.js, impacting 1,000+ global users.• Took over daily standups sprint planning occasionally in absence of IM• Participated in 30+ code reviews and architecture discussions, delivering high-quality, production-ready solutions with 90%+ test coverage.• Integrated CI/CD workflows with Git and Jenkins, improving release efficiency by 30%.• Resolved vulnerabilities and supported production troubleshooting.• Collaborated with architects and testers to deliver production-ready solutions in sprint cycles.• Participated in Agile ceremonies, backlog grooming, and sprint cycles to deliver incremental value.
Developed and maintained 9+ microservices using Angular and Node.js, impacting 1,000+ global users.
Took over daily standups sprint planning occasionally in absence of IM.
Participated in 30+ code reviews and architecture discussions, delivering high-quality, production-ready solutions with 90%+ test coverage.
Integrated CI/CD workflows with Git and Jenkins, improving release efficiency by 30%.
Resolved vulnerabilities and supported production troubleshooting.
Collaborated with architects and testers to deliver production-ready solutions in sprint cycles.
Participated in Agile ceremonies, backlog grooming, and sprint cycles to deliver incremental value.
Developed and evaluated machine learning models to predict groundwater contamination trends using real-time data from IoT sensors.
Focused on model accuracy, validation, and continuous tuning, ensuring performance and achieved 93% accuracy meeting the platform’s real-time decision-making requirements.
Participated in sprint planning, contributing to delivery planning and backlog refinement.
Saaf Water is an open-source platform designed to address groundwater contamination by leveraging IoT devices for automated water quality monitoring. It integrates IBM Cloud and Watson services to provide real-time updates to communities and authorities, suggesting purification methods when needed. By analyzing collected data, it predicts water quality trends, reducing reliance on manual or lab testing for approximate assessments, and ensuring safer drinking water for all.CONTRIBUTION• Developed and evaluated machine learning models to predict groundwater contamination trends using real-time data from IoT sensors.• Focused on model accuracy, validation, and continuous tuning, ensuring performance and achieved 93% accuracy meeting the platform’s real-time decision-making requirements.• Participated in sprint planning, contributing to delivery planning and backlog refinement.
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