Sales Development Representative

Overview

You prospect into companies that use modern data warehouses (Snowflake, Databricks, BigQuery) and have marketing or customer data challenges. Your goal is booking discovery calls for AEs with marketing ops directors, data engineering leaders, or CDOs. You're educating prospects on a relatively new category (Composable CDP) so most people you reach haven't heard of Hightouch yet.

Role Snapshot

Company Context

Stage: Series C+ (503 employees, well-funded)

Size: 503 employees

Growth: Active hiring across all functions, Forbes #8 Best Startup Employer

Market Position: Category leader in Composable CDP / Reverse ETL - but still educating the market on what that means

GTM Reality

Pipeline Sources:

• 90% Cold outbound - You're building lists of companies that have data warehouse job postings, are hiring marketing ops roles, or show up on intent data for terms like "customer data platform" or "marketing automation"
• 10% Warm inbound follow-up - Sometimes you'll get lukewarm inbound leads that aren't ready yet, and you nurture them with targeted sequences

SDR/AE Structure: Pool of SDRs supporting a team of AEs; you're assigned specific accounts/verticals

SE Support: None at SDR stage - you need to be able to explain the value prop without deep technical help

Competitive Landscape

Main Competitors: Segment, Census, build-it-yourself approaches

How They Differentiate: Broadest integrations (250+ tools), AI decisioning features, warehouse-native approach

Common Objections: "We already use Segment", "Our data team can build this", "Not a priority right now"

Win Themes: Speed to value without engineering bottlenecks, marketing team self-service, no data copying

What You'll Actually Do

Time Breakdown

Prospecting (60%) | Follow-up/Qualification (30%) | Internal (10%)

Key Activities

• Building target lists: You research companies using LinkedIn Sales Navigator, job boards (companies hiring for "Snowflake engineer" or "Marketing Ops Manager"), and intent signals. You're looking for companies with $50M+ revenue, modern data stacks, and marketing complexity (multi-channel campaigns, e-commerce, etc.).
• Cold calling: 40-60 calls per day to marketing ops and data leaders. Most don't pick up. When they do, you have about 30 seconds to explain what Hightouch does before they decide if it's relevant. Common response: "What's a Composable CDP?" - you need a crisp answer.
• Email sequences: You send personalized emails referencing their tech stack ("saw you're using Snowflake and Braze"), specific use cases ("syncing audience segments from your warehouse to ad platforms"), or pain points ("marketing waiting on data engineering for new segments"). Response rates are 2-5% if your messaging is sharp.
• LinkedIn outreach: Connect requests and messages to warm people up before calling. About 30% of your meetings come from multi-channel sequences (email + LinkedIn + call).
• Qualifying warm responses: When someone replies "tell me more", you jump on a quick 10-min call to confirm they have the right tech stack, a real use case, and budget. About half of responses are tire-kickers or too early-stage ("we're still setting up Snowflake").

The Honest Reality

What's Hard

• Category education over cold outreach: You're not selling a familiar product like Salesforce or HubSpot. You're explaining a new approach to customer data that most people haven't heard of. Lots of confused prospects who don't immediately get why they need this.
• Technical gatekeeping: Data engineering leaders are protective of their turf and skeptical of marketing tools. They'll say "we can build this in-house" or "this seems like unnecessary complexity." You need to know enough about data architecture to push back credibly.
• Low response rates: You're reaching senior people (directors, VPs) who are slammed. Your emails compete with 50 other vendors. Even great messaging gets ignored. Expect 2-3% email response rates and 20-30% call connect rates.
• Long qualification cycles: Even when someone is interested, they often need to "talk to our data team" or "finish our current project" before they're ready for a demo. Deals you book in January might not close until Q3.

What Success Looks Like

• Booking 15-20 qualified meetings per month that AEs accept (meetings where the prospect has Snowflake/Databricks, a real use case, and can make a decision in the next 3-6 months)
• 30-40% of your meetings turn into active opportunities for AEs
• Keeping your pipeline warm with 40-50 active prospects in various nurture stages

Who You're Selling To

Primary Buyers:

• Director/VP of Marketing Operations at B2C brands (e-commerce, consumer apps, fintech)
• Head of Data Engineering or Analytics at fast-growing companies
• Marketing technology managers at mid-market B2B software companies

What They Care About:

• Can we get our warehouse data into marketing tools without waiting on engineering? (speed/autonomy)
• Will this replace our current CDP or add to the stack? (cost/complexity)
• How hard is setup? (they've been burned by other data tools)

Requirements

• 0-2 years in SDR/BDR role, ideally in martech or data infrastructure
• Comfortable with technical concepts - you should understand what a data warehouse is and why companies use them
• High resilience to rejection (most calls/emails get ignored)
• Strong research skills to identify good-fit accounts
• Ability to explain complex concepts simply over phone/email