Junior Data Engineer

1. BI & Superset Platform Development (30%)

• Design, build and maintain Superset dashboards and reports based on approved business KPI definitions.
• Configure Superset datasets, metrics, filters, and user roles / row-level security.
• Optimize query and dashboard performance through caching, pre-aggregated tables and SQL tuning.

2. Data Pipelines & Data Modelling (20%)

• Assist in developing, operating, and maintaining end-to-end data pipelines (ETL/ELT),
• Write, test, and maintain transformation, validation, and enrichment logic using Python and SQL.
• Ingest data from various internal databases, event streams, and third-party APIs.
• 3. Data Quality, Monitoring & Troubleshooting (30%)
• Monitor pipeline health, logs, and alerts
• Validate and reconcile dashboard figures against source systems and official business reports, then investigate and resolve any discrepancies.
• Carefully troubleshoot and resolve script errors, performance lags, and data discrepancies.
• 4. Stakeholder Collaboration & Documentation (20%)
• Collaborate cross-functionally to clarify stakeholder requirements and KPI logic, and support smooth, reliable releases to production.
• Provide basic guidance to business users on using Superset.
• Maintain technical documentation, the data dictionary and metric definitions.

Requirements

• Bachelor’s degree in computer science, Software Engineering, Information Technology, or related discipline. 0 to 1 year of professional or internship experience in data engineering, software engineering, or backend development.
• Fresh graduates with relevant capstone projects, coursework, or internships are welcome to apply.
• Strong fundamentals in Python and SQL, with the patience and ability to step-debug code and resolve query performance issues.
• Data-first" mindset: A commitment to understanding business context, data semantics, and schema relationships before writing code.
• Basic understanding of modern data design patterns, such as the Medallion Architecture (Bronze, Silver, Gold layers).
• Ability to build clean, intuitive business intelligence dashboards and charts.
• Basic familiarity with Git version control, Linux/Bash commands, and container basics (Docker).
• Comfortable reading/writing technical documentation, communicating, and participating in stakeholder meeting with English communication.
• Special Skills
• High attention to detail: Meticulous regarding data accuracy, data types, and edge-case handling.
• High coachability: An attentive listener who follows architectural direction, respects code  conventions, and implements feedback from the lead effectively.
• Ownership & discipline: Follows established guidelines and takes pride in clean,maintainable, production-ready work.
• Nice to have
• Direct hands-on experience with Apache Superset (or tools like Metabase, Tableau, Power BI).
• End-to-end BI projects (academic, personal, or internship) covering raw ingestion to visualization.
• Exposure to cloud platforms (AWS, GCP, or Azure).
• Familiarity with workflow orchestrators (e.g., AWS Step Functions, Apache Airflow).