Senior Analytics Engineer

This role is a hybrid role. Employees will be in the office at our Bellevue, WA location 3 days a week and remote 2 days a week.

About Esper

Esper revolutionizes device management by redefining what it should be: a driver of business growth. With advanced and modern capabilities, automation replaces outdated workflows, re-provisioning becomes obsolete, and managing by exception transforms efficiency, resulting in increased efficiency, improved ROI, and bolsters security for device fleets of all sizes. Esper has been recognized as number 735 on Inc. Magazine's  fastest-growing private companies in America, and 133 on the 2024 Deloitte Technology Fast 500.

Some of the world’s most innovative brands, like Google, Doordash, Taco Bell, Clinical ink, SF 49ers, and Intelity, rely on Esper to deliver exceptional device experiences. Esper partners with the leading mobile device hardware manufacturers, solution providers, and distributors globally.

About the role

We are hiring a full-time Sr. Analytics Engineer who sits within the Business Operations team and supports both operational execution and strategic decision making.

The Sr. Analytics Engineer is a core contributor to the Analytics and Business Operations functions. This role is responsible for building and governing data models, developing and maintaining robust machine learning frameworks, and enabling reliable data informed decision making and insights across the company.

who

What you'll do

• Design, build, and maintain analytics ready data models using SQL
• Own core fact and dimension tables supporting revenue, sales, and operational analytics
• Partner with stakeholders to develop, operationalize, and evolve core business metrics
• Prevent metric drift by centralizing logic in governed models

• Model and transform data from primary sources, including Postgres and Salesforce
• Orchestrating complex workflows and ETL pipelines
• Collaborate with Business Operations and Data Engineering to onboard and govern new data sources
• Account for source system nuances, timing differences, and edge cases in models and forecasting solutions

• Lead AI/ML initiatives, including developing, tuning, validating, and deploying predictive models (e.g. churn, forecasting)
• Iterate on existing ML frameworks to improve accuracy and prevent model drift
• Drive operational and strategic decision-making through trusted analytics assets and forecasts

• Implement and maintain data governance standards and best practices
• Design and maintain data quality and alerting systems to streamline operations and proactively detect issues
• Document models, metrics, and analytics workflows clearly and consistently

What We're Looking For

• 3 to 6 years of experience in Analytics Engineering, Analytics, Business Intelligence, or Data Engineering
• Expert level SQL skills with experience working in a modern cloud data warehouse platform such as Snowflake, Big Query, or Redshift;
  Databricks experience is a plus
• Experience implementing and optimizing scalable data warehouse infrastructure to support reliable analytics and forecasting workloads
• Python scripting experience to streamline and automate analytics and BI processes
• Experience supporting BI tools (Tableau), by delivering governed, analytics ready datasets and partnering with stakeholders to design, build, and maintain reliable, well structured dashboards
• Demonstrated experience building and refining effective ML models used to drive business decisions
• Strong understanding of the analytics engineering development cycle - data modeling, version control, CI/CD, documentation, testing, and codebase best practices

• Comfortable operating with a high degree of ownership and autonomy, taking responsibility for outcomes while partnering with others to deliver shared solutions
• Strong understanding of Salesforce data and how to extract, transform, and model it for analytics
• Experience supporting revenue, growth, or operational forecasting
• Familiarity with SaaS metrics…