Amazon RedshiftBigQueryMySQLPostgresSQLTableauAIGenerative AILarge Language ModelsAnalyticsLookerSnowflakeRedshiftSaaSLeadershipProduct ManagementCommunication
About this role
Role Overview
Acquiring, organizing, measuring, and interpreting data from primary and secondary sources to support our analytic initiatives.
Supporting the identification of product opportunities and performance trends using appropriate analytical techniques.
Delivering custom data solutions to our partners (business customers), providing them with valuable insights and actionable recommendations.
Collaborating with data and software engineering teams to support the growth and reliability of Peek’s data warehouse and data marts.
Assisting in the preparation and delivery of analytics projects, ensuring high-quality and timely completion.
Working closely with our product management, marketing, and success teams to enhance the revenue capabilities of our flagship SaaS booking platform, leveraging data-driven insights.
Supporting internal financial initiatives by collaborating with our finance department, providing data analysis to inform financial decision-making.
Actively participating in the analytics community at Peek, sharing best practices, contributing to analytics forums, and staying up to date with industry trends and advancements.
Experimenting with AI tools, including large language models (LLMs), to increase the efficiency of analysis, automate repetitive tasks, and improve how insights are generated and communicated.
Requirements
1-2 years of experience working on deriving insight from large, semi-structured datasets as a product or data analyst in a SaaS software organization.
1-2 years of experience writing SQL against large and complex data sets.
1-2 years of experience working with web and mobile analytics platforms such as MixPanel, Amplitude, Google Analytics, Heap, Pendo, etc.
1-2 years of experience working with data analytics/visualization tools such as Looker, Tableau, Google Data Studio, etc.
Experience working with analytical (Redshift, Snowflake, BigQuery, etc.) or transactional databases (Postgres, MySQL, etc)
Experience using generative AI or LLMs to streamline workflows, surface insights faster, or enhance internal reporting and decision-making.
Clear communication skills and the ability to explain insights to non-technical stakeholders.
Familiarity with the product development life cycle and how data informs prioritization, iteration, and success measurement.
Ability to manage multiple tasks or projects simultaneously with guidance and clear priorities from leadership.