Data Engineer

Portcast is a venture-backed, Singapore-based logistics technology startup building a real-time transportation visibility platform for global supply chains. We help shippers, manufacturers, and logistics service providers turn data into decisions - and decisions into measurable business impact.

Our platform goes beyond visibility. Portcast enables action at scale by surfacing the right risks early, helping teams prevent detention and demurrage, accelerate exception management, and close invoices faster with built-in evidence. We turn visibility into outcomes: reduced costs, improved operational control, and more predictable supply chains.

Founded in 2018 and backed by leading technology investors, we are building for an industry at a critical inflection point of digital transformation. Our team of software engineers, data scientists, and logistics experts is on a mission to make supply chains not just visible, but decisively actionable - end to end.

About the Role:

We are looking for a Data Engineer who can own and scale critical data systems powering logistics intelligence and customer-facing products. This role requires deep expertise in data engineering, strong product intuition, and the ability to translate complex data into reliable, actionable insights.

You will play a key role in building robust pipelines, ensuring data quality at scale, and enabling both internal teams and enterprise customers with high-quality, production-grade data.

What You'll Do:

• Design and scale end-to-end data pipelines to process large-scale logistics and supply chain data.
• Build and optimize ETL/ELT workflows using SQL, Python, and orchestration tools like Airflow.
• Own data delivery for enterprise customers, ensuring accuracy, reliability, and SLA adherence.
• Develop highly performant data models and transformations in Snowflake and cloud data warehouses.
• Lead data migration and architecture improvements, optimizing cost and performance across systems.
• Build data validation and quality frameworks to ensure high reliability and reduce production issues.
• Automate reporting and analytics workflows, significantly reducing manual effort and operational overhead.
• Work with APIs, third-party integrations, and semi-structured data (JSON) to ingest and normalize data.
• Collaborate closely with product and engineering teams to implement business logic and data-driven features.
• Debug and resolve production issues across data pipelines and backend systems.
• Enable self-serve analytics through clean, well-structured datasets and dashboards.

To Thrive in This Role, You Must Have:

• Bachelor's or Master's Degree in Computer Science, Analytics, Business, or equivalent work experience in the field.
• At least 4+ years of experience in analytics engineering, data engineering, or backend systems.
• Strong expertise in SQL and Python, with a focus on large-scale data processing.
• Hands-on experience with cloud platforms (AWS, GCP, Azure).
• Deep experience with data warehousing (Snowflake, BigQuery) and performance optimization.
• Experience with Airflow or similar orchestration tools for managing workflows.
• Strong understanding of data modeling, ETL/ELT design, and pipeline architecture.
• Experience working with APIs and semi-structured data (JSON).
• Familiarity with Docker and distributed data systems.
• Strong debugging and problem-solving skills in production environments.
• Ability to work cross-functionally and translate business requirements into scalable data solutions.

Good to Have:

• Experience with web scraping frameworks (Selenium, Scrapy).
• Experience in logistics, shipping, or supply chain domains.
• Experience with BI tools (Metabase, Tableau).
• Exposure to AI/LLM-based analytics workflows or internal tooling.

What's In It For You:

• Work on high-scale, real-world problems in global supply chain intelligence.
• High ownership across the full data lifecycle - from ingestion to product impact.
• Opportunity to shape data systems in a fast-growing, product-first startup.
• Exposure to modern data stack and evolving AI-driven analytics workflows.
• Direct visibility of your work impacting customers and business outcomes.

Our CORE Values Guide Everything We Do:

• Curiosity: We continuously explore and improve.
• Ownership: We take responsibility for outcomes, not just tasks.
• Raising the Bar: We push for scalable, efficient systems.
• Effective: We focus on measurable business impact.