• 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 • 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 • 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) •
• 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 • 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 •
• Work on exciting SaaS projects and sophisticated features and functionalities that will make a big impact in the industry • Join a well-oiled and stable rockstar expert team with enterprise-grade processes • Non-hierarchical, entrepreneurial and collaborative organisation • Partner closely with business stakeholders • Competitive compensation and generous benefits, including comprehensive insurance and ample leave • Access to formal training through face-to-face sessions, coaching and Intrepid Academy •
• Python • SQL • Apache Airflow • Google BigQuery • Snowflake • Azure Synapse • Databricks • MySQL • Postgres • dbt • StarRocks • ClickHouse • Cube.dev • Looker Studio • Apache Superset • pandas •
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