At Tecton, we solve the complex data problems in production machine learning. Tecton’s feature platform makes it simple to activate data for smarter models and predictions, abstracting away the complex engineering to speed up innovation.
Tecton’s founders developed the first Feature Store when they created Uber’s Michelangelo ML platform, and we’re now bringing those same capabilities to every organization in the world.
Tecton is funded by Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins, along with strategic investments from Snowflake and Databricks. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
We are looking for an experienced SDR Manager to build and lead a high-performing Sales Development team that consistently delivers a strong pipeline of qualified opportunities. As a player-coach, you will balance hands-on prospecting with strategic leadership, developing a best-in-class SDR function. You will implement proven processes, leverage cutting-edge sales technologies (including GenAI), and collaborate closely with marketing and sales leadership to optimize pipeline generation. If you're data-driven, passionate about coaching, and eager to scale a results-oriented SDR team, this role is for you!
Responsibilities
- Build & Lead an SDR Team – Recruit, train, and develop a team of 3-5 SDRs to exceed NBM and SQO quotas.
- Drive Pipeline Growth – Implement multi-channel outreach strategies and optimize messaging to improve lead conversion.
- Optimize SDR Operations – Establish best practices for lead routing, tracking, and reporting in Salesforce, Outreach, and HubSpot.
- Collaborate with Marketing & Sales – Work cross-functionally to align messaging and ensure a seamless lead-to-opportunity process.
- Leverage Data & Technology – Use analytics and automation (including GenAI) to refine prospecting strategies and improve efficiency.
Qualifications
- Proven experience as an SDR Manager
- Deep understanding of modern sales development techniques, including multi-channel prospecting.
- Strong ability to coach, mentor, and develop SDR talent.
- Expertise in sales analytics, pipeline tracking, and data-driven decision-making.
- Experience working with technical buyers (ML engineers, data scientists, tech leaders) and communicating complex solutions effectively.
Tecton values diversity and is an equal-opportunity employer committed to creating an inclusive environment for all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics. If you would like to request any accommodations from the application through to the interview, please contact us at [email protected].
This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
Top Skills
What We Do
Founded by the team that created the Uber Michelangelo platform, Tecton provides an enterprise-ready feature store to make world-class machine learning accessible to every company.
Machine learning creates new opportunities to generate more value than ever before from data. Companies can now build ML-driven applications to automate decisions at machine speed, deliver magical customer experiences, and re-invent business processes.
But ML models will only ever be as good as the data that is fed to them. Today, it’s incredibly hard to build and manage ML data. Most companies don’t have access to the advanced ML data infrastructure that is used by the internet giants. So ML teams spend the majority of their time building custom features and bespoke data pipelines, and most models never make it to production.
We believe that companies need a new kind of data platform built for the unique requirements of ML. Our goal is to enable ML teams to build great features, serve them to production quickly and reliably, and do it at scale. By getting the data layer for ML right, companies can get better models to production faster to drive real business outcomes.
