Mattermost is an open source platform for secure collaboration across the entire software development lifecycle. Hundreds of thousands of developers around the globe trust Mattermost to increase their productivity by bringing together team communication, task and project management, and workflow orchestration into a unified platform for agile software development.
Founded in 2016, Mattermost’s open source platform powers over 800,000 workspaces worldwide with the support of over 4,000 contributors from across the developer community. The company serves over 800 customers, including European Parliament, NASA, Nasdaq, Samsung, SAP, United States Air Force and Wealthfront, and is backed by world-class investors including Battery Ventures, Redpoint, S28 Capital, YC Continuity. To learn more, visit www.mattermost.com.
We value high impact work, ownership, self-awareness and being focused on customer success. If these values match who you are, we hope you'll learn more about working at Mattermost and apply!
In this fast-paced role, you will be part of the team that is responsible for enterprise data strategy initiatives: leveraging data for actionable business outcomes, improving operational performance, and delivering greater analytics insight for Finance, G&A, and Mattermost as a whole. You are the catalyst and facilitator of Data Quality and Financial Analytics for the organization, orchestrating and overseeing the adoption of best practices across all global business units. You will be instrumental in executing against the strategic roadmap, governance, and quality controls for Finance and G&A data across the end-end data lifecycle. You will partner with Data Engineering, R&D analytics, and S&M analytics teams managing Snowflake data warehouse, building and maintaining ETL and data ingestion processes, and providing assistance to key stakeholders and Executives.
- Proactively identify revenue-impacting issues, investigate root causes, and drive them to resolution across Finance, HR, product, and engineering teams
- Partner with the Data Engineering team to ensure relevant data is centralized into Snowflake, modeled for performant analytics, and meeting our high-quality standards
- Own the entire development process for our finance, HR, and recruiting analytics reporting. This includes meeting with internal customers to understand their needs, partnering with data engineering to centralize dispersed data, understanding the core data models, writing code to enrich and manipulate data, and designing and iterating dashboards
- Be hands with monitoring tools, work with large data sets, and provide insights into our Financial performance. - 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
- Gather and interpret data; generate, track and monitor business KPIs and conduct regular readouts to stakeholders including leadership
- Effectively communicate insights and make recommendations and decisions in line with business objectives
- Project manage the end to end process to triage and resolve revenue anomalies; this includes leading investigation efforts to identify root causes which may include changes in sales pipeline, product releases and/or system related issues
- Become an expert at using a variety of internal data systems and assist with automating and scripting repetitive tasks where needed
- BA, BS or MS with a focus on economics, statistics, math, computer science or a related quantitative discipline
- Minimum 3+ years of demonstrated hands-on technical experience in data analysis utilizing Excel, Looker, and SQL
- Minimum 3+ years of business data analytics experience
- Critical thinker with the ability to analyze and evaluate situations objectively; capable of making recommendations and decisions based on what’s best for the business goal at hand
- Basic project management skills to identify and track tasks and dependencies as well as assess and control risks
- Detail-oriented with the ability to see the “big picture” and frame opportunities
- Process-oriented, with an appreciation for following and maintaining documentation including run-books and trackers
- Capable of working with large, complex datasets
- Comfortable (even happy!) spending hours at a time poring over spreadsheets, creating data visualizations, and performing analyses
Nice to haves:
- Data visualization skillsExperience with additional programming languages and technologies such as Python Scripting
- Data mining experience utilizing BI tools such as Looker and Snowflake
- Comfortable working with a variety of different tools and scripting languages and flexible in your choice of key technologies in the data analytics stack
- Ability to work independently in a small, globally-distributed remote team
- Strong written and verbal communication skills and a proven ability to work with engineers, data analysts and non-technical stakeholders across all departments of an organization.