Reporting / Data Engineer

Qualification: 

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or related field.
• 3–5 years of experience in Reporting Engineering, ETL development, data warehousing, or BI data preparation.
• Experience supporting production data pipelines and operational reporting environments.
• Have experience in eCommerce, retail, CRM, loyalty, campaign management, OMS, or customer data platforms will be plus. 
• Have experience with cloud data platforms such as Alibaba Cloud, AWS and GCP.
• Experience with modern data stack tools such as Airflow, Spark, Kafka, Flink, or similar.
• Experience with data lake architecture using landing, bronze, silver, and gold layers.
• Understanding of API-based data ingestion and event-driven data pipelines.
• Experience with data observability, lineage, and monitoring tools.
• Knowledge of data privacy, masking, encryption, and access control.
• Willing to WFO in Tangerang 
• Willing to placed in Start Up Fintech company 

Job Description:

1. Source System Data Integration

• Work with application teams to understand source systems, database structures, APIs, event logs, and business data flows.
• Design and develop data extraction processes from transactional systems such as eCommerce, CRM, Loyalty, OMS, Campaign Management, Finance, HR, or other enterprise applications.
• Build reliable data pipelines to push data from source systems into the Data Warehouse.
• Support batch, near-real-time, and scheduled data ingestion requirements.
• Handle data from multiple formats and sources, including relational databases, APIs, flat files, logs, and third-party platforms.

2. Data Warehouse Pipeline Development

• Develop, maintain, and optimize ETL/ELT pipelines.
• Transform raw source data into clean, structured, and analytics-ready datasets.
• Implement staging, transformation, validation, and loading processes.
• Maintain data models such as fact tables, dimension tables, aggregated tables, and reporting marts.
• Ensure pipelines are scalable, maintainable, and production-ready.

3. Operational Reporting Support

• Build and maintain datasets required for daily, weekly, and monthly operational reports.
• Work with business teams to understand reporting requirements and convert them into data logic.
• Support reports related to sales, orders, customers, campaigns, loyalty, inventory, fulfillment, SLA, service performance, and operational KPIs.
• Ensure operational reports are accurate, timely, and reconciled with source systems.
• Help troubleshoot reporting discrepancies and data mismatches.

4. Data Quality and Reconciliation

• Implement data validation checks, reconciliation rules, and exception reporting.
• Monitor data completeness, accuracy, consistency, and timeliness.
• Identify root causes of data issues and coordinate fixes with application, database, or business teams.
• Maintain audit logs, load status, and error-handling mechanisms for data pipelines.

5. Performance and Reliability

• Optimize SQL queries, stored procedures, data loads, and reporting datasets.
• Monitor pipeline performance and resolve failures within agreed SLAs.
• Improve data pipeline reliability through automation, alerting, and proper error handling.
• Support production incidents related to data availability, reporting delays, or incorrect data.

6. Documentation and Governance

• Document source-to-target mappings, data lineage, business rules, transformation logic, and report definitions.
• Maintain technical documentation for pipelines, jobs, schedules, dependencies, and recovery procedures.
• Follow data governance, security, access control, and compliance standards.
• Ensure sensitive business and customer data is handled securely.