Senior Data Engineer

Samsung Food (Whisk)
RemotePosted 10 April 2026

Job Description

Senior Data Engineer About Samsung Food At Samsung Food (you might know us as Whisk), we are pioneering the future of everyday care and health — helping individuals and families around the world live better through connected, proactive, and personalized experiences. Our mission is to connect food, health, and home across the Samsung ecosystem, turning data from your devices into personalized guidance that supports you and your loved ones. We work at the intersection of AI, nutrition, behavior change, and digital health. The Samsung Food app was included in Google Play’s Best of 2020 Everyday Essentials list, has been regularly featured on the Apple App Store, and was nominated for a 2021 Webby Award. We’ve also launched Vision AI, which recognises food and meals using our global Food Genome, and developed deep integrations with Samsung Health and SmartThings. We are a remote-first team of more than 100 people in over 30 countries, united by our commitment to innovation and impact. As part of Samsung Electronics, we combine the agility of a startup with the scale of the world’s largest consumer electronics company. Join us and help build technology that improves daily life for tens of millions of people across phones, wearables, TVs, and kitchen appliances in the years to come. Learn  more about how we’ve shaped a high-performing global team over the past 14 years. About the Role We’re looking for a Senior Data Engineer to join our Data Platform team and help shape the foundations of how data is collected, modeled, governed, and served across Samsung Food. This is a high-impact senior individual contributor role for someone who enjoys building reliable systems, designing scalable data models, and raising engineering standards across the organization. You’ll work on the core platform that enables analytics, experimentation, product insights, operational use cases, and future intelligent data products. You’ll thrive in this role if you enjoy combining hands-on engineering with technical leadership: designing robust pipelines, improving platform reliability, guiding modeling standards, and partnering closely with product, analytics, and engineering teams to make data trustworthy and actionable. What You’ll Do Build and evolve our data platform: design, develop, and maintain scalable batch and streaming data pipelines using Python, SQL, ClickHouse, Airflow, Kafka, dbt, and dlt. Model data for scale and usability: design clean, well-documented, and sustainable data models using dimensional modeling and Kimball principles, enabling self-serve analytics and consistent business metrics. Own transformation workflows: build and maintain transformation layers in dbt, improving testing, documentation, lineage, and reliability across our analytics stack. Optimize data storage and query performance: work with ClickHouse to design efficient schemas, improve performance, and ensure cost-effective access to high-volume datasets. Improve platform reliability and operability: strengthen orchestration, observability, data quality, and failure recovery across pipelines and services running in Kubernetes. Drive engineering standards: establish best practices for data development, testing, deployment, versioning, and monitoring across the platform. Champion data governance: help define and implement data governance principles, including data quality, ownership, lineage, consistency, and documentation. Partner across teams: work closely with product managers, analysts, data consumers, and software engineers to understand business needs and translate them into scalable technical solutions. Lead through expertise: contribute to architecture decisions, mentor other engineers, raise the technical bar, and influence how data engineering is practiced across Samsung Food. What You Bring Strong (4+ years) experience in data engineering, with a track record of building and operating production-grade data platforms in modern product or tech ... (truncated, view full listing at source)
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