We're building the future of Real-Time Merchant Analytics at Shopify!
As a Staff Engineer you'll be at the forefront of reimagining how merchant data flows through modern streaming architectures. This isn't your typical infrastructure role – you'll be crafting solutions that challenge conventional approaches to data processing at global scale.
What Makes This Exciting?
You'll work across multiple languages and technologies – Java, Ruby, Python, SQL, Flink, and ClickHouse – choosing the right tool for each challenge, model data elegantly, and turning data pipeline development into a configuration exercise rather than a coding marathon.
You'll tackle fascinating problems: How do you architect lightning-fast real-time modeling that seamlessly combines data from multiple tables? How do you handle late-arriving data in distributed streams? What's the most elegant approach to backfill terabytes while maintaining real-time processing?
We embrace AI and LLMs to accelerate repetitive tasks, freeing you to focus on the creative problem-solving that makes this work truly rewarding.
If you love turning "impossible" requirements into beautiful solutions, this is your playground.
What You'll Do
Architect, build, and refine high-performance streaming infrastructure tailored to large-scale, real-time merchant analytics.
Develop tools and frameworks to boost platform efficiency, scalability, and developer experience across the team.
Collaborate with cross-functional teams to integrate streaming systems with Shopify's broader data ecosystem.
Partner with product and data teams to influence the technical roadmap and shape the future of merchant analytics.
Mentor and uplevel engineers on the team, fostering an environment of innovation and technical excellence.
What You'll Need
Extensive experience in data infrastructure engineering, particularly in building and scaling real-time data platforms.
Strong knowledge of Apache Flink or similar stream processing frameworks (Kafka Streams, Spark Streaming).
Proficiency in multiple programming languages (Java, SQL required; Python, Ruby a plus).
Experience with analytical databases like ClickHouse or BigQuery.
Strong understanding of containerization (Docker, Kubernetes).
Deep expertise in handling distributed systems challenges: late-arriving data, exactly-once semantics, backfill strategies, and data consistency.
Outstanding problem-solving skills with a focus on complex technical challenges at scale.
A collaborative mindset and the ability to thrive in a diverse, dynamic team environment.