Senior Analytics Engineer – GTM

Sigma Computing•San Francisco, CA

3h•$150,000 - $180,000•Onsite

About The Position

With 3.5x in ARR and a sales workforce growing +63% annually over the past 3 years, Sigma is looking for someone to join the rocketship and contribute their data chops to scale our Go-To-Market initiative! As a Senior Analytics Engineer on the Data Platform team, you would collaborate closely with Sales, Marketing, RevOps, and Sales Enablement and drive large-scale initiatives to expand market reach, improve sales efficiency, and identify operational gaps. If you’re passionate about analytics engineering and the future of analytics, let’s chat!

Requirements

Expertise in SQL and dbt, comfortable with at least one programming language (e.g. Python, R, Scala, etc), and experience using a cloud data warehouse (Snowflake or Databricks preferred)
Strong visualization skills (Sigma experience preferred - you will use Sigma every day!)
Experience using git for version control
Comfort with the ambiguity that comes with working in a fast-paced environment
GTM domain expertise
Strong desire to ideate and implement new processes to make the team more efficient
Highly organized with the ability to quickly identify and prioritize opportunities for optimal ROI
Excellent communication skills, with the ability to explain complex data insights to non-technical stakeholders
Positive attitude and ability to receive and provide objective and constructive feedback

Responsibilities

Build and maintain commissions data models and workbooks to facilitate payroll processing & inform future comp plan designs.
Design, develop, and maintain core data models as well as create engaging visualizations using Sigma to support GTM initiatives, ensuring a high level of data accuracy and usability.
Partner with your stakeholders to understand their requirements and deliver data solutions attuned to their current needs while ensuring scalability. Clearly scope, track, execute, and communicate on projects.
Define and implement data engineering standards and best practices. Provide guidance and support to other team members to ensure adherence to these standards, promoting high-quality data processes and governance.
Be the in-house expert on sales analytics and enable the field to leverage insights in a meaningful way.