Product Analytics Engineer

Data Engineering:
• Collaborate with stakeholders to understand data requirements and design and implement scalable data pipelines.
• Develop and maintain ETL processes to ensure timely and accurate data availability for analytics purposes.
• Optimize and troubleshoot existing data pipelines for performance and reliability.


Product Analytics:
• Partner with product teams to define and implement tracking mechanisms for key product metrics.
• Analyze user behavior, product usage, and other relevant data to provide insights that drive product improvements.
• Create and maintain dashboards and reports to communicate analytical findings to stakeholders.


Data Quality and Governance:
• Implement data quality checks and validation processes to ensure the accuracy and integrity of our data.
• Contribute to the development and enforcement of data governance policies and best practices.


Collaboration:
• Work closely with data scientists, business analysts, and other stakeholders to understand their data needs and deliver solutions.
• Collaborate with cross-functional teams to integrate analytics into product development processes.


Technology Stack:
• Utilize tools and technologies within the Kong data ecosystem, including Snowflake, DBT, Fivetran, etc. .

What we look for:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• 4-6 years of experience as an Analytics Engineer or similar role (data analyst, data scientist or data engineer).
• Experience with product analytics, including defining and tracking relevant metrics.
• Strong proficiency in data engineering, ETL processes, and database management.
• Proficiency in SQL, any scripting language (Python, R) and a data visualization tool like Tableau, or Power BI.
• Familiarity with DBT docs for data transformation.


Preferred Skills:
• Familiarity with Snowflake, and reverse ETL tools is a plus
• Experience in B2B (Business-to-Business) and/or SaaS business