Muhammad Habibi Email & Phone Number

Jakarta, Indonesia

Notes: Role ended due to company-wide layoff.Description:- Led a team of data engineers and analysts to design and implement scalable data architecture and analytics services.- Achieved a 70% reduction in monthly cloud data infrastructure costs through data migration and optimization initiatives.- Designed and implemented data architecture in GCP from scratch, leveraging MySQL, PostgreSQL, and Metabase.- Migrated data warehouse from GCP (BigQuery) to AWS (Athena).- Designed and implemented data architecture in AWS from scratch, utilizing MySQL, PostgreSQL, CockroachDB, AWS, Kafka (MSK), and Metabase.- Developed and rolled out self-service analytics solutions, empowering non-technical teams to access and utilize data independently.

Notes: Role ended due to company-wide layoff.Description: Designed and built a real-time data pipeline in GCP from scratch, ensuring efficient and reliable data flow to support business operations.

Jakarta, Indonesia

Description:- Designed and implemented a hybrid data platform combining Vanilla Hadoop and Google Cloud Platform (GCP) to support large-scale data processing and analytics.

Jakarta, Indonesia

Notes: Company laid me off due to pandemic Covid-19Description: Led 4 ppl (DE &BI) to design, implement & improve data infrastructure, real-time data ingestion, data warehouse, data mart, data quality, analytics dashboard & ad-hoc tasks (using kanban). Also, manage good data governance, deliver insights to Mgmt team, reached OKR & KPI, budget & resource planningKey Projects:- Data Warehouse Development: Designed & built on top of Bigquery from scratch- Online & Offline Database Cost Reduction: Reach 50%- Near Real-time Data Ingestion & Visualization: Using Google Cloud Platform Products & visualized near real-time data using Lambda Architecture concept- Data Quality: Gathered & Troubleshoot DQ use cases following principles, also monitored it using Power BI- KPI Dashboard: Designed & built using Power BI

Jakarta

Description: Led 5 ppl to manage DaaS platform & end-to-end data flow from the online database (enterprise RDBMS), offline data (data warehouse & data mart), and data visualization. Offline data platform (batch & real-time data ingestion, data warehouse) built on top of Hadoop and Spark in AliCloudKey Projects: - Data Warehouse Development: Developed DWH methodology using Internet Financial Technology Data Models- KPI Dashboard: Built KPI dashboard along with BI team- Realtime Data Analytics: Realtime data visualization to support big event/ campaign- User Behavior Analysis: Integrated all behavior transaction from all channels that user transact & user demographic- Digital Marketing Analytics: Data Integration from 3rd party to get LTV analysis (organic & paid for installs, register & active), analysed CPX (Cost Per Install, Cost Per Complete Registration, Cost Per Active / Success Transaction)- Data Governance: Applied good data governance & security

Description: Led 5 ppl supporting product development team and data acquisition from both offline or online dataKey Projects:- Data Integration: Data validation and cleansing and MDM using Talend (Banking Industry)- Data Integration: Replaced old Data Warehouse (Oracle & SQL Server) to use Hive by using Talend Platform (Banking Industry)- ISO 27001 Certification : Responsible in incident management, but also practically manage data management, user privileges, data confidentiality, user access matrix

Jakarta, Indonesia

Description: Consultant for Big Data analytics projects (covered tech tools such as enterprise RDBMS, data lake, data warehouse, hadoop, BI tools) Key Projects: - User Profiling: Data prep & user profiling using Netezza SQL (Telco industry)- User Segmentation: Prepared and managed database from SQLServer to process in Hadoop Impala and Hive, in order to create client user segmentation. The total data size is 6 TB and the biggest amount of rows is 2 bio rows in one table (Insurance Industry)- Data Integration: Collect and convert structured data into unstructured data, in order to process in Hadoop Hbase (FMCG Industry)- Data Preparation and Enrichment: Apply data cleansing, matching and enriching in Oracle (Banking Industry)