Mattermost is hiring a
Data Analytics Engineer

Summary

Mattermost is hiring a data enthusiast to solve data analytics and engineering problems for Marketing, Sales, Product, and Engineering organizations. The Data Engineer will build and maintain a data engineering stack, work closely with teams to understand customer trends and analyze user activities, and provide insights that impact the health of the business.

Requirements

• 5+ years of demonstrated experience in data analysis or analytics engineering
• Experience with schema design, data modeling and metadata management
• Experience applying Software Engineering best practices to data analytics including CI/CD, version control, etc
• Experience with building and maintaining data pipelines
• In-depth knowledge of (at least) one data warehouse system
• Experience with building reports to various stakeholders
• Strong SQL skills
• Excellent written and verbal communication skills
• Demonstrable teamwork skills and resourcefulness

Responsibilities

• Proactively identify data-related issues, investigate root causes and drive them to resolution across Marketing, Sales, Product, and Engineering functional areas
• Work with the other Data Engineering team members to ensure relevant, high-quality, raw data is ingested into our data warehouse and correctly modeled for performant analytics
• Build and maintain models that provide the analytics that will help the functional teams predict results and report on performance
• Participate in the development process for Marketing, Sales, Product and Engineering analytics reporting
• Be hands-on with monitoring tools, work with large data sets, and provide insights into performance(e.g. Engineering)
• Become an expert at maintaining a variety of internal data systems and automate and script repetitive tasks where needed
• Support other larger-org teams regarding the most effective ways of collecting the data and enforce its quality
• Provide guidance to functional leaders on KPIs, metrics and business decisions including accurate analysis of user and business data
• Educate and help empower other larger-org team members on data-related aspects