Data Engineer

Intrepid Asia, Jakarta, Indonesia

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Published on 22 September 2026 · first appeared in our records on 22 September 2026.

Stable posting: first seen on 22 September 2026, with no abnormal reposting.

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Who we are Intrepid Asia is a leading Ecommerce and Digital Solutions Provider in South East Asia. We offer end-to-end omni-channel ecommerce management, Livestreaming, Video production & Affiliate Management for Social Commerce, plus full funnel Digital Marketing Services and advanced Market Intelligence, all powered by state-of-the-art in-house Technology to our client base of leading international brands across all key marketplaces and social platforms in all 6 SEA countries. Brands love our regional presence, our excellent data-driven, growth-focused services, enabled by the industry's strongest team, and our advanced marketing and tech capabilities. We are growing rapidly, and as the exclusive partner of Flywheel in SEA,  we offer many exciting opportunities to work with leading brands across multiple categories and key industry players. By joining us, you will work on the cutting edge of digital and social commerce in SEA, and experience what it takes to drive a successful ecommerce business end-to-end. The part you will play We are looking for a motivated Junior Data Engineer to join our Data Engineering team and support the reliability and growth of our data pipelines and warehouses. You'll work closely with senior data engineers, the Data Engineering Manager, and the BI Data Analyst team, building hands-on experience across our stack while contributing to real production pipelines that power decision-making for our brand clients across SEA. Our current stack includes Google BigQuery, StarRocks, Airflow, dbt, Cube.dev (semantic layer), Looker Studio, and Apache Superset. This is a great opportunity for someone with a couple of years of data engineering experience who wants to deepen their skills in a fast-paced, agile environment and grow toward more senior ownership over time. As a Junior Data Engineer, you will • Data Pipeline Development • Build, maintain, and troubleshoot ETL/ELT pipelines orchestrated with Apache Airflow under the guidance of senior engineers. • Write and optimize SQL transformations across StarRocks and Google BigQuery. • Support building and maintaining in Airflow job and dbt models for data transformation, following team standards for testing and documentation. • Support ingestion of data from multiple marketplace and social commerce platforms into our warehouse. • Data Quality & Monitoring • Implement and maintain data quality checks against defined metrics and SLAs for assigned datasets. • Monitor pipeline runs, investigate failures, and escalate or resolve issues with support from senior team members. • Collaboration & Learning • Work with analysts and senior data engineers to understand data requirements and translate them into pipeline logic. • Participate in Agile ceremonies (Scrum/Kanban) sprint planning, stand-ups, retros. • Follow and help apply team conventions for pipeline standardization, naming, and documentation. • Continuously build proficiency with the team's modern data stack and DataOps practices (version control, code review, testing). Must-have: • Bachelor's degree in Computer Science, Engineering, or a related technical field. • 2+ years of hands-on experience in data engineering, data pipelines, or a closely related role. • Proven Python & SQL proficiency • Hands-on experience with Apache Airflow or a comparable workflow orchestration tool. • Working proficiency in Python (e.g., pandas, scripting for data workflows). • Familiarity with cloud data warehouses (Google BigQuery preferred; Snowflake, Azure Synapse, Databricks, or similar also considered). • Familiarity with OLTP databases such as MySQL or Postgres. • Basic understanding of ETL/ELT design patterns and data modelling concepts. Nice-to-have: • Exposure to dbt (or similar transformation tools) for building and testing data models. • Exposure to OLAP databases (StarRocks, ClickHouse, or similar). • Familiarity with a semantic layer tool (e.g., Cube.dev) or BI/reporting tools (Looker Studio, Apache Superset). • Experience working in an Agile/Scrum environment. • Eagerness to learn, take ownership of assigned tasks, and grow into a more senior data engineering role.