Facilitate data-informed decision-making across the product and engineering teams
Partner with product & engineering teams understand important business problems, then own the full lifecycle of data-driven solutions: analysis, metric definitions, transformation pipelines in dbt, experimentation, measurement, data story-telling and, most importantly, influencing decisions
Collaborate with Product, Research, Engineering, Customer Success and others to provide data products to allow them to better measure the impact of their work and find new opportunities
Work with data engineers on our team to help build our new Lake House in Databricks in your area of expertise and document vital context about our data that can be used by both stakeholders and AI tools
Provide leadership in how we use product analytics tools like Amplitude to make decisions
Be a key voice in making data-driven decisions in our software development lifecycle
Increase your impact by continuously learning and evolving your workflows as AI technology matures. Form opinions that help Jellyfish support its customers in their AI journeys.
Enable your stakeholders to have a bigger impact through the use of AI in their own analytics workflows. As necessary, build the data tools they need, be their expert-in-the-loop, or influence them to adopt new workflows.

Strong knowledge of SQL (preferably Databricks, Snowflake, or Redshift)
Experience with data quality best practices and building data models in dbt
Experience using Python (numpy, pandas, sklearn, etc.) across exploratory data analysis or predictive modeling
Proven ability to influence and ship with product and engineering teams, especially in B2B SaaS environment
Proven ability to influence product and engineering leaders with data-driven insights
Strong perspective on using the appropriate data solution for the business need at hand
Strong perspective on scaling product analytics solutions, including tools like Amplitude, across a company for both technical and non-technical users
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Growth mindset and flexibility to adapt to changing technology and workflows

Lead Product Data Analyst

Key skills