Senior Data Engineer

Role details

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. SENIOR DATA ENGINEER At Snowflake, we are building the future of the data-driven enterprise. We are looking for a Senior Data Engineer who brings deep technical craft, strong ownership instincts, and the ability to operate across the full data lifecycle — from raw ingestion to production-ready data products. This is not a role for someone who executes tickets. You will design and build the data infrastructure that powers internal decision-making and external product capabilities, working at the intersection of data engineering, platform thinking, and stakeholder alignment. You will own complex technical decisions, set the bar for data quality and governance, and contribute to a data platform that scales with the business. The person we are looking for combines engineering rigour with pragmatic judgement — someone who can solve for today while building for the future, and who raises the standard of the teams they work within. AS A SENIOR DATA ENGINEER AT SNOWFLAKE, YOU WILL: - Design, build, and launch production-ready data models and pipelines that scale effectively across the enterprise data lifecycle — from ingestion through transformation, modelling, and consumption - Own complex system design decisions end-to-end, evaluating tradeoffs and documenting architectural choices clearly - Implement enterprise-grade data governance frameworks and maintain rigorous data quality standards across the platform - Develop and optimise data ingestion processes from diverse enterprise sources - Align with the Product roadmap to build tools for the data platform and provide feature feedback as an internal customer zero - Mature requirements gathering practices and apply Agile methodologies to data product development — including stand ups, sprint planning, reviews, and retrospectives - Lead quality assurance efforts by defining testing strategies, identifying risks, and ensuring timely resolution of technical issues - Build strong relationships with stakeholders at all levels — from executive to operational — translating ambiguous requirements into well-scoped technical work - Proactively adapt to changing business requirements while maintaining solution integrity OUR IDEAL SENIOR DATA ENGINEER WILL HAVE: Education & Experience - Bachelor's degree in Computer Science, Information Systems, or a related field with emphasis on system design, distributed systems, or data warehousing — or equivalent practical experience - 5–8 years of hands-on experience building and operating production data pipelines, data models, and platform infrastructure at scale Technical Skills — Required - Expert-level SQL and strong Python skills, with experience in performance tuning, query optimisation, and schema design for large-scale analytical workloads - Hands-on experience with Snowflake — including Snowpark, dynamic tables, data sharing, Snowflake Cortex, and cost optimisation techniques - Deep expertise in DBT — advanced modelling patterns, testing frameworks, macro authoring, and project-level governance on Snowflake - Strong proficiency with Apache Airflow — DAG design, operator customisation, dependency management, and operational best practices - Solid understanding of dimensional modelling, data vault, and semantic layer design Technical Skills — Preferred - Experience designing data pipelines and feature engineering workflows for ML model training and inference - Exposure to ML tooling ecosystems: MLflow, Feature Stores, vector databases, or LLM serving infrastructure - Experience with Snowflake Cortex AI functions or similar LLM API integrations for data enrichment and AI-ready data product development Technical Skills — Desired - Cloud infrastructure (AWS, Azure, or GCP) — including infrastructure-as-code and cost management - Knowledge of streaming ingestion patterns (Kafka, Snowpipe Streaming) and real-time data architecture - Familiarity with data contract frameworks and schema registry tooling Professional Skills - Strong system design and architectural reasoning — able to evaluate tradeoffs, explain decisions, and document designs clearly - Excellent written and verbal communication skills; comfortable presenting technical recommendations to both engineering and non-technical stakeholders - Collaborative problem-solver who actively elevates team practices, not just individual output - Self-directed with strong ownership instincts — drives problems to resolution without requiring ongoing prompting - Effective at navigating ambiguity and distilling requirements into well-scoped technical work Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com http://careers.snowflake.com