Junior Data Engineer

Role decriptions:
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).