Why This Job is Featured on The SaaS Jobs
This Data Analyst role stands out in a SaaS context because it sits at the intersection of Product, GTM, and business decision-making, where subscription metrics and usage signals typically shape priorities. With the position housed in Engineering and grounded in a modern warehouse and lakehouse setup, the work aligns with how SaaS companies increasingly operationalise analytics as part of the core platform rather than a reporting add-on.
For a long-term SaaS career, the value is in building fluency across the full analytics loop: defining stakeholder questions, translating them into data models and dashboards, and maintaining trust through data quality. Experience with SQL, Python, Snowflake or Databricks, and version control maps well to common SaaS data stacks, making the skill set portable across product-led and sales-led organisations that rely on shared metrics and consistent definitions.
The role is best suited to an analyst who prefers close collaboration and can move between technical detail and business framing without losing precision. It will fit someone who enjoys building reusable reporting assets, working with large datasets, and being accountable for reliability as much as insight, particularly in an on-site environment where stakeholder proximity is high.
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
Employment Type
Full time
We are hiring a Data Analyst to join our data team, which drives cross-company insights and supports decision-making across GTM, Product, and Business functions.
Responsibilities:
Analyze and interpret data to support strategic and operational decisions
Build and maintain reports, dashboards, and visualizations used across the company
Work closely with stakeholders to understand business needs and translate them into data solutions
Ensure data quality, consistency, and reliability across systems
Requirements:
3+ years of experience as a Data Analyst
Strong analytical skills and attention to detail
Proficiency in Python and SQL
Experience working with large-scale data environments
Hands-on experience with Snowflake and/or Databricks – required
Familiarity with AI coding tools (e.g., Claude Code, Cursor)
Experience working with Git
Tech stack:
Education:
Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field – required
Master’s degree in a relevant field – preferred
Preferred qualifications:
Experience working with large and complex datasets
Strong business understanding and ability to translate data into actionable insights
This role is suited for someone who wants to be at the core of how data informs decisions across the organization.
