Why This Job is Featured on The SaaS Jobs
This Senior Data Engineer role sits at a core SaaS intersection: product usage, analytics, and the data science workflows that turn platform telemetry into decisions. With Snowflake as the central warehouse layer and cloud services in scope, the position reflects how modern SaaS companies standardise data access across teams while keeping performance and governance front of mind.
For a SaaS career, the durable value here is building repeatable data foundations that support multiple downstream consumers, from dashboards to experimentation and modelling. Ownership of cost optimisation and performance tuning is particularly relevant in subscription businesses where margins are influenced by infrastructure efficiency. The emphasis on data quality checks, SLAs, and access controls also maps closely to the operational maturity expected as SaaS products scale their customer base and internal reporting needs.
This role suits an engineer who prefers platform thinking over one-off analyses, and who enjoys partnering with product and data science stakeholders to translate requirements into reliable pipelines. It also fits someone comfortable balancing build work with operational stewardship, including governance and troubleshooting, while contributing to shared standards through version control and deployment workflows.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.
We are looking for a skilled Snowflake Data Engineer to join our Product and Data Science team. The ideal candidate brings a solid background in data engineering, with deep expertise in Snowflake and cloud technologies.
In this role, you will design, build, and maintain robust data pipelines, ensuring our data infrastructure is scalable, reliable, and efficient. You will partner closely with product and data scientists, providing tools, automation, and best practices to accelerate their work, improve data quality, and ensure consistency across pipelines and dashboards.
Additionally, you will play a critical role in cost optimization for data operations, owning efficient data modeling and pipeline performance. This position is also key in building and scaling our enterprise data warehouse, helping to shape the future of our data ecosystem.
Responsibilities
Design, develop, and maintain scalable data pipelines using Snowflake and cloud technologies.
Own and manage cost optimization for Product and Data Science team operations.
Optimize pipelines for performance, reliability, and efficiency.
Build and maintain dashboards and reporting platforms using Streamlit.
Collaborate with cross-functional teams to gather requirements and deliver robust data solutions.
Work with modern AI tools, including Cursor, to accelerate development.
Implement data governance, security best practices, and access control policies.
Develop and enforce data quality checks, SLA monitoring, and dependency tracking.
Utilize version control systems (e.g., Git) and manage deployment workflows.
Proactively troubleshoot and resolve data-related issues.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or a related field.
Proven hands-on experience with Snowflake, including data modeling, ETL/ELT development, and performance tuning.
Advanced proficiency in Python, with experience scripting and automating data workflows.
Demonstrated experience building Streamlit applications integrated with Snowflake.
Strong command of SQL for complex data querying and analysis.
Familiarity with cloud platforms such as AWS, Azure, or GCP, and services like S3, Redshift, or BigQuery.
Strong problem-solving and communication skills.
Ability to thrive both independently and as part of a collaborative, fast-paced team environment.
Preferred Qualifications:
Master’s degree in Computer Science, Engineering, or a related discipline.
Strong understanding of data warehousing principles, architecture, and best practices.
Experience working within Agile development frameworks (e.g., Scrum, Kanban).
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
