Yohan Ivandri Yuana

Operations Associate

West Jakarta, Jakarta, Indonesia5 yrs 2 mos experience

AI ML PractitionerHighly Stable

Key Highlights

Over 5 years of experience in IT and data engineering.
Expert in designing and managing ETL processes.
Strong communicator translating technical solutions for stakeholders.

Stackforce AI infers this person is a Data Engineer with expertise in Fintech and SaaS environments.

Contact

Skills

Core Skills

Data IntelligenceEtlData WarehousingReporting AutomationApplication SupportData Engineering

Other Skills

Microsoft Power BISQLPythonFTPAPI MonitoringData IntegritySQL OptimizationSQL ServerAirflowDockerMicrosoft FabricDatawarehouseHadoopData StoreData Security

About

IT professional with over 5 years of experience in Management Information Systems (MIS), IT Application Support, and data processing. Skilled in designing and managing ETL processes, building and maintaining data pipelines, and implementing data warehousing solutions following Medallion Architecture principles. Experienced in monitoring API integrations and automating reports using SQL and Python. Strong communicator, able to translate complex technical solutions into clear insights for non-technical stakeholders and present data-driven recommendations to executives. Demonstrated leadership in coordinating cross-functional projects, mentoring junior staff, and taking ownership of critical initiatives. Adept at prioritizing tasks based on business urgency to deliver timely solutions supporting both operational and strategic goals.

Experience

5 yrs 2 mos

Total Experience

5 yrs

Average Tenure

2 mos

Current Experience

Pt bank nationalnobu tbk (nobubank)

Management Information Systems Supervisor

Mar 2026 – Present · 2 mos · Tangerang, Banten, Indonesia · On-site

Data IntelligenceMicrosoft Power BI

Id/x partners

Project Based-Virtual Intern: Data Engineer

Nov 2025 – Nov 2025 · 0 mo · Jakarta, Indonesia · Remote

Build and maintain end-to-end data pipelines using Python, SQL Server, Airflow, and Docker
Develop incremental ETL processes for efficient and reliable data ingestion
Design and manage data warehouse layers (staging, core, and mart)
Create and maintain dimension and fact tables for analytical workloads
Prepare data marts for analytics, including daily summaries and customer reports
Develop stored procedures for reporting and downstream consumption
Optimize SQL queries, indexing, and partitioning to improve performance and reliability

PythonSQL ServerAirflowDockerData Engineering

Pt mega central finance

2 roles

Management Information System

Promoted

Jul 2023 – Mar 2026 · 2 yrs 8 mos · Jakarta, Indonesia · On-site

Responsible for extracting and transforming ad-hoc datasets to fulfill diverse business and user requests, ensuring timely and accurate data delivery for decision-making.
Utilize SQL, Python, and stored procedures to process both small and large datasets efficiently, applying techniques such as query optimization and data chunking when working with heavy loads.
Design, develop, and maintain automated ETL pipelines using SQL and Python to streamline data movement and transformation processes.
Create reporting automation workflows integrated with FTP and MPX delivery systems, automatically distributing reports to business users and management.
Continuously enhance automation projects to increase efficiency, reduce manual effort, and ensure high data accuracy and reliability across reporting systems.

SQLPythonETLData WarehousingReporting Automation

Application Support

Mar 2021 – Jul 2023 · 2 yrs 4 mos · Jakarta, Indonesia · On-site

Collaborate with users to understand data requirements and validate outputs, maintaining consistency across OLTP and mirrored databases.
Monitor end-to-end transaction processes for batching, billing, and termination flows, ensuring reliable API-based data integration between internal systems and banking platforms, including scheduler monitoring, error resolution, and data regeneration when required
Provide comprehensive back-end support by performing DDL/DML operations, resolving system data issues, and maintaining data integrity across multiple environments.
Optimize queries within application systems and automated reporting pipelines to improve performance and reduce processing time.
Troubleshoot and correct failed report generations or inaccurate data results, ensuring smooth operation of daily reporting activities and system stability.

API MonitoringData IntegritySQL OptimizationApplication Support