To learn more, visit www.mattermost.com

Mattermost is seeking a passionate data enthusiast to solve data analytics and engineering problems for the Marketing, Sales, Product and Engineering organizations. As a data-driven organization, Mattermost relies on our data team to drive insights into various areas, ensure data quality across systems, iterate on current key business metrics, and dive into complex datasets to answer business-critical questions.

In this role, you will help build and maintain a highly-performant data engineering stack and work closely with the Marketing, Sales, Product and Engineering organizations to deeply understand customer trends, analyze user activities, product adoption, and sales results in order to surface insights that impact the health of the overall business. If you are data-obsessed, love connecting the dots, thrive in an iterative environment, and aren’t afraid to get your hands dirty, this is the role for you.

About Our Tools

● Tool Stack: dbt, Airflow, Snowflake, Looker, Rudderstack, Stitch, Hightouch, Salesforce, Google Analytics, Clearbit, Google Sheets/Excel, Kubernetes, etc.

● Coding Languages: SQL, Python, LookML

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 our Marketing, Sales, Product and Engineering analytics reporting. This includes meeting with internal customers to understand their needs, understanding the core data models, writing code to enrich and transform raw data to analytics data and designing and iterating dashboards
• Be hands-on with monitoring tools, work with large data sets, and provide insights into our performance(e.g. Engineering). This includes writing queries to access data, performing analysis, utilizing your technical expertise as well as a variety of internal tools and/or collaborating with other teams as needed
• 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

Required Background/Skills:

• 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

Mattermost is an EEO Employer. We are a remote-first, open source company.

We are constantly working towards adding more countries/regions to this list, but first we need to make sure we are compliant with local laws and regulations, which takes time. 

Mattermost is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people from all walks of life. We don't discriminate against staff or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!