SDR Manager

Overview

You manage a team of SDRs who cold call and email data engineers, analytics directors, and CDOs at enterprises. They're trying to book meetings for AEs to pitch Starburst Galaxy (managed data lakehouse) or Starburst Enterprise (self-hosted). You're accountable for qualified pipeline generation, coaching technical messaging, and building repeatable outbound motions in a space where prospects already have Snowflake, Databricks, or a homegrown Trino setup.

Role Snapshot

Company Context

Stage: Late-stage private (533 employees, backed by well-known VCs based on company profile)

Size: 533 employees

Growth: Actively hiring for SDR leadership - signal they're scaling sales org

Market Position: Challenger in a crowded space (Snowflake, Databricks, AWS Athena, Google BigQuery all compete). Built on open-source Trino, differentiate on separation of compute/storage and multi-cloud flexibility.

GTM Reality

Pipeline Sources:

• 25% Inbound - whitepapers on data lakehouses, webinars, conference leads. Quality varies - lots of tire-kickers researching alternatives to their current stack.
• 65% Outbound - cold calling/emailing into enterprises with data lakes, Hadoop migrations, or teams evaluating modern data stacks. Lots of LinkedIn research to find the right persona (not always clear who owns data platform decisions).
• 10% Partners/Community - Trino user community, AWS/Azure marketplace interest.

SDR/AE Structure: SDRs book meetings, AEs run full cycle with SE support. You're managing the front end of a long, technical sale.

SE Support: AEs have dedicated or pooled SEs for demos/POCs - SDRs don't typically involve SEs until handoff.

Competitive Landscape

Main Competitors: Snowflake (cloud data warehouse), Databricks (lakehouse platform), Dremio (data lakehouse), AWS Athena/Redshift, homegrown Trino deployments, legacy data warehouses.

How They Differentiate: Open-source Trino foundation (no lock-in), query federation across multiple sources without moving data, better price/performance claims vs. Snowflake on certain workloads.

Common Objections: "We already have Snowflake/Databricks," "Our data engineers built Trino in-house," "Why not just use Athena if we're on AWS?", "This sounds like another tool to manage."

Win Themes: Multi-cloud flexibility, avoid vendor lock-in, faster time-to-insight without ETL, cost savings on compute, open-source community backing.

What You'll Actually Do

Time Breakdown

Coaching/1-on-1s (30%) | Deal Reviews/Pipeline (25%) | Process Building (20%) | Cross-functional (15%) | Recruiting/Hiring (10%)

Key Activities

• Daily standup and deal reviews: Listen to call recordings, review email sequences, coach SDRs on technical positioning ("What's a data lakehouse?" "Why not just use Snowflake?"). A lot of time spent teaching reps how to speak to data engineers without sounding like a generic SaaS SDR.
• Building and refining outbound plays: Create new sequences for specific personas (data engineering managers migrating off Hadoop, analytics leaders frustrated with Snowflake costs). Test messaging. Pull reports on what's working. Adjust.
• Pipeline accountability meetings: Weekly/monthly reviews with Sales leadership and RevOps on qualified meetings booked, meeting-to-opp conversion, and where SDRs are falling short. You own the number.
• Cross-functional alignment: Syncs with Marketing on lead quality and ICP, with Sales on feedback from AEs ("These meetings aren't qualified," "We need more enterprise logos"), with RevOps on dashboards and territory assignments.
• Coaching for career growth: 1-on-1s where you're developing SDRs for promotion to AE roles. Some reps want to close deals, others want to stay in prospecting - you're managing different career paths.
• Hiring and ramping new SDRs: Screening candidates, sitting in on interviews, building onboarding plans. When someone joins, you're teaching them the tech stack, the talk tracks, and how to navigate internal systems (SFDC, Outreach, LinkedIn Sales Nav).

The Honest Reality

What's Hard

• Technical product in a crowded market: Your SDRs are calling data engineers who already have solutions and don't love sales calls. Teaching reps how to talk about query federation, Iceberg tables, and Trino without sounding clueless is real work. Lots of "I don't understand what we do" conversations early on.
• Long feedback loops: SDRs book a meeting, AE runs a 4-9 month sales cycle. You don't know if the meeting was actually good for months. Hard to course-correct quickly.
• Pressure on pipeline generation: Sales leadership is watching your team's contribution to overall pipeline. If AEs miss quota, they'll look at SDR meeting quality. If Marketing isn't delivering enough inbound, you're expected to make up the gap with outbound. The number is always there.
• Balancing coaching with execution: You want to develop people, but you also have a quota. Some days you're hopping on calls yourself or rewriting sequences because the team is behind. Player-coach means you don't fully let go of the doing.
• Retention and promotion timing: Good SDRs want to promote to AE within 12-18 months. If you don't have openings or they're not ready, they leave. You're constantly hiring and training.

What Success Looks Like

• Your team consistently books 40-60 qualified meetings per month (8-10 per SDR if you have 5-6 reps).
• Meeting-to-opp conversion rate is 25-35% (AEs turn your meetings into real pipeline).
• SDRs are hitting or exceeding individual meeting quotas without burning out.
• You promote 1-2 SDRs to AE roles per year - shows you're developing talent.
• AEs and Sales leadership trust your team's meetings (not complaining about quality).

Who You're Selling To (What Your SDRs Target)

Primary Buyers:

• VP/Director of Data Engineering (owns data infrastructure, evaluating modern stacks)
• Chief Data Officer / Head of Analytics (strategic buyer for data platform investments)
• Data Platform Architects (technical evaluator, often the gatekeeper)

What They Care About:

• Performance and cost ("Can we query faster and cheaper than Snowflake?")
• Flexibility and avoiding vendor lock-in ("Can we use this across AWS, Azure, GCP?")
• Integration with existing stack ("Does this work with our Iceberg tables and S3 buckets?")
• Ease of migration ("How hard is it to move off our current setup?")
• Open-source credibility ("Is this just a commercial wrapper on Trino, or do you contribute back?")

Requirements

• 2-4 years managing SDR/BDR teams, ideally in enterprise tech (data, infrastructure, or technical SaaS)
• Experience coaching reps on complex, technical products - you need to teach SDRs how to talk to data engineers
• Track record of hitting/exceeding pipeline generation targets in an outbound-heavy environment
• Comfortable building processes from scratch (sequences, playbooks, onboarding docs) - this isn't a fully baked SDR org
• Strong cross-functional skills - you'll be in a lot of meetings with Sales, Marketing, RevOps, and Enablement
• Experience with SFDC, Outreach/SalesLoft, LinkedIn Sales Navigator, and reporting/dashboards
• Willingness to get tactical - you'll be reviewing calls, writing emails, and jumping on calls yourself when needed
• Ideally, some familiarity with data infrastructure, analytics tools, or cloud platforms (helps with credibility when coaching technical messaging)