Staff Engineer - Real-Time Merchant Analytics

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.