Senior Software Engineer, Stats & Analytics - Data Platform

Staff/Senior Software Engineer, Stats & Analytics - Data Platform

Canada;
United States

Stack Adapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI‑powered Stack Adapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward‑thinking marketers choose Stack Adapt to orchestrate high‑impact campaigns across programmatic advertising and marketing channels.

We’re seeking a Senior Engineer to join our Stats & Analytics Data Platform team — the group responsible for building and operating the infrastructure that powers data at scale across Stack Adapt. Our systems process terabytes of data daily, serving both real‑time and batch use cases. The data platform ensures that data is fresh, accurate, and cost‑efficient so that analytics, machine learning, and product teams can rely on trustworthy, governed datasets.

Stack Adapt is a Remote First company, and we are open to candidates located anywhere in the United States or Canada.

• Design and build scalable data pipelines, batch jobs, and streaming processes that power analytics and machine learning.
• Implement and optimize data storage systems (warehouses, lakes, analytical databases) with a focus on reliability, lineage, and governance.
• Develop tools and frameworks to support data orchestration, ETL workflows, and big data processing.
• Collaborate with engineers, data scientists, and product managers to align platform capabilities with business needs.
• Ensure data systems meet requirements for quality, scalability, and cost efficiency in cloud environments.
• Contribute to technical discussions, code reviews, and system design sessions.
• Take ownership of features and projects, driving them from concept to production.

• Strong background in software engineering, data engineering and distributed systems, ideally at scale (terabytes+).
• Hands‑on experience with modern data warehouses, lakes, and compute/storage technologies (e.g., Snowflake, Pinot, TiDB, Spark, Airflow, Kafka, Trino/Presto).
• Experience designing and building robust ETL pipelines and real‑time streaming processes.
• Solid understanding of data governance, lineage, and cost optimization in cloud environments.
• Ability to write clean, maintainable, and performant code in production systems.
• Strong problem‑solving skills and ability to collaborate across teams.

As a Senior Engineer on the Data Platform team, you’ll help shape the backbone of Stack Adapt’s data ecosystem. The reliability and scalability of the systems you build will directly influence how quickly and confidently teams across the company can innovate using data.

• Highly competitive salary
• Retirement/401K/Pension Savings globally
• Competitive Paid time off packages including birthday’s off!
• Access to a comprehensive mental health care program
• Health benefits from day one of employment
• Work from home reimbursements
• Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto
• Robust training and onboarding program
• Coverage and support of personal development initiatives (conferences, courses, books etc)
• Access to Stack Adapt programmatic courses and certifications to support continuous learning
• An awesome parental leave program
• A friendly, welcoming, and supportive culture
• Our social and team events!

Stack Adapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability (or superpower) status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome  you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.

About Stack Adapt

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