---
title: 'Growth Marketer at MotherDuck'
canonical: 'https://feeny.ai/job/growth-marketer-motherduck-san-francisco-2ek5n4asd1ff'
type: 'job'
last_seen: '2026-09-13'
---

# Growth Marketer at MotherDuck

- **Company:** MotherDuck
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-08
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/motherduck/2ba10571-dba9-46b4-8626-5d2cb43504a0

## Job description

## About MotherDuck

Don’t let the quirky name fool you: At MotherDuck, we’re on a mission to make data warehousing fun, frictionless, and ducking awesome for developers and data practitioners building blazing fast internal and customer-facing analytics experiences. We're building a cloud-hosted version of DuckDB, working hand-in-hand with the creators of the fastest-growing and fastest-improving query engine on the planet. Unlike other databases, MotherDuck was architected to unify local development with cloud operations to bridge the gap between software and data engineering workflows. Our team is a mix of thoughtful, passionate, and empathetic data industry veterans.

## About the role

We're looking for a creative yet technical marketer... someone who can write the ad copy, build the segment, run the test, and then navigate based on the quantitative signals. You'll own growth end to end: paid, organic, lifecycle, experimentation, across every channel we touch, not just one lane. Right now the biggest opportunities on our plate are:

- Conversion hacking across the site and landing pages
- Webinars, from topic strategy and audience segmentation through to pipeline and signup conversion
- Social hacking, working alongside product marketing and DevRel
- AEO (answer engine optimization)
- Re-engagement audience hacking for people who've gone quiet
- Segment testing at scale, from lookalikes to usage-pattern and conversion-pattern based audiences, feeding Google, Meta, LinkedIn and beyond

But the role isn't limited to that list. You'll have a hand in every part of growth and lifecycle marketing, and you're expected to bring your own ideas about where the next win is, not just execute a queue.

## What you'll do

Own the full funnel

- Work both motions: self-serve signups that need to activate and convert, and accounts that need to become sales-qualified pipeline. Neither one is a side project.
- Take plays from spec to live: audience, signal, message, channel, landing page, conversion. You get support on strategy and full ownership of execution.

Run experiments like they matter

- Define the metric, the guardrail, and the sample size before anything ships, not after the data looks interesting.
- Do your own analysis: cohort curves, funnel step conversion, segment cuts, time-to-activation, cost per activated account, cost per SQA. SQL against the warehouse, not a screenshot of a dashboard.
- Know the difference between a real lift and noise, and say so out loud, even when it's your own play that lost.

Build with agents, not just tools

- Build agent workflows daily: research, list building, lookalike testing, personalization, creative variants, landing page drafts, competitor monitoring, post-test analysis.
- Point agents at our stack (Clay, HubSpot, Apollo, our marketing MCP) so plays run with you supervising, not clicking through every step.
- Prototype fast and for real: a scraper, a scoring pass, a signal listener, a one-off page, instead of scoping it out to someone else.

Segment and test relentlessly

- Wire intent signals (Clay intent, product usage, DuckDB and community activity, job changes, hiring and tooling signals) into plays that feed both self-serve signup and pipeline.
- Build LinkedIn and other channel automations: engage motions, Clay-synced ad audiences, retargeting off product and content behavior.
- Run a real volume of tests across the funnel: landing pages, signup flow, activation moments, lifecycle and in-product email, outbound messaging, list sources. A high test count is the job, not a sign you're thrashing.

Own social, nurture, and event presence

- Own social strategy end to end, including managing the social agency.
- Own email nurture content and design, with your manager weighing in on strategy and voice.

Scale what works, kill what doesn't

- Hand proven winners to marketing ops to productionize, then move on to the next unproven thing.
- Flag plateaus early instead of keeping a play alive just because it's yours.

## What we're looking for

- Hands-on experience with Claude Code or similar LLM tooling. This isn't a "used ChatGPT once" bar, we mean you actually build with agents.
- A resume with real quantitative results: pipeline contribution, PLG or SLG conversion metrics, cost per activated account/SQA, that kind of thing.
- Cross-channel growth experience with genuine technical chops (comfortable in SQL, can run your own cohort analysis and basic stats on test results).
- Background at a high-growth company (data/AI space preferred, but a Ramp-equivalent is fine too).
- 1-3 years in growth, performance marketing, demand gen, or a scrappy generalist marketing role, or a track record of building growth things on your own that speaks for itself.
- Great writing, and credibility with a developer and data audience.
- A bias toward shipping. If you see something no one owns, that's an opening, not a blocker.

What people should be saying if you're doing ducking awesome

- Your manager: "I stopped worrying about whether the test was set up right months ago."
- Sales: "Growth's signals are actually why we booked that meeting."
- Marketing ops: "I just productionized three of their plays this month and they're already onto the next thing."
- A candidate who interviewed and didn't get the offer: "That was one of the more thoughtful processes I've been through."
- You, to yourself: "That play flopped, here's exactly why, here's what I'm testing next."

Please Apply Does this role sound appealing to you, but you’re missing some of the requirements or don’t quite think you’re qualified?  Please apply anyway. Research has shown that underrepresented groups in technology often shy away from roles which aren’t a 100% match. We aim to build a diverse team and will strongly consider applicants who bring many of the requirements plus have other experiences which round out their qualifications. MotherDuck is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. MotherDuck is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities.

## About MotherDuck

## Company Overview
- **One-liner**: MotherDuck is a serverless, cloud-native data warehouse built on DuckDB that delivers sub-second query performance and AI-native analytics for humans, agents, and applications.
- **Entity Type**: Private (Series B; $100M total funding)
- **Headquarters**: Seattle, Washington, United States (with hubs in San Francisco, New York, and Amsterdam)
- **Founded**: 2022
- **Founders**: Jordan Tigani (co‑founder & CEO, former Google BigQuery founding engineer) in partnership with DuckDB creators Hannes Mühleisen and Mark Raasveldt (DuckLabs)

## Core Business
- **Industry**: Data Infrastructure and Analytics (serverless cloud data warehouse)
- **Target Customers**: B2B – data teams, SaaS companies building customer‑facing analytics, AI/agent developers, and enterprises wanting to cut data warehouse costs
- **Mission**: “Collapse the distance between question and answer” – make it easy for anyone to explore data without waiting on data teams

## Products & Services
- **MotherDuck (Cloud Data Warehouse)**: Serverless, fully managed DuckDB service. Every user/agent gets an isolated DuckDB instance (“Duckling”) that spins up in 100ms and shuts down when idle. Supports petabyte‑scale data in S3, GCS, Azure (including Iceberg/Delta Lake). 5–10x cheaper than Snowflake/BigQuery.
- **DuckLake**: The fastest, simplest lakehouse – open table format that stores metadata in a SQL database instead of thousands of files, for petabyte scale and 100x faster metadata operations.
- **Dives**: AI‑generated interactive visualizations. Ask natural‑language questions, get live charts with sub‑second performance. Persistent and shareable – no separate BI tool needed.
- **Flights**: Agent‑native data pipelines – scheduled Python jobs for ingestion, enrichment, and transformation, built and deployed through the MCP server.
- **MCP Server (Model Context Protocol)**: Connects AI agents (Claude, ChatGPT, Cursor, etc.) to MotherDuck databases with fuzzy catalog search, query guidelines, and cost isolation.
- **Data Sharing**: Create shareable, read‑only snapshots of databases (cross‑org collaboration).
- **Read Scaling**: Replicas for high‑concurrency BI and multi‑user workloads.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: $40M annual revenue (LinkedIn estimate, 2026) + $100M total funding ($12.5M Seed, $35M Series A, $52.5M Series B)
- **Notable Investors/Partners**: Andreessen Horowitz, Redpoint, Felicis (investors). Technology partners include Airbyte, Fivetran, dbt, Metabase, Tableau, Hex, Power BI, LangChain, LlamaIndex, Anthropic, Monte Carlo, and 59+ others.
- **Growth Signals**: Headcount grew 54.4% YoY (to ~97 employees); active job postings increasing month over month (37.5% monthly trend, 11 open roles as of mid‑2026); strong ecosystem integration with 59 technology and 11 consulting partners.

## Competitive Advantages
- **Built on DuckDB**: Inherits the blazing‑fast, in‑process query engine that improves 20% per version, while adding serverless cloud capabilities.
- **Hypertenancy Architecture**: Each user/agent gets an isolated DuckDB instance – no noisy neighbors, no workload management, and no cost spikes from AI agents.
- **Extreme Cost Efficiency**: Customers routinely cut warehouse costs 5–10x vs. Snowflake/BigQuery by running small queries on small machines.
- **AI‑Native from Day One**: MCP server, Dives, Flights – designed for agentic and natural‑language analytics, eliminating the need for separate BI or orchestration tools.
- **Seamless Embedding**: SaaS companies can give each end customer an isolated analytics backend; 100ms spin‑up and zero idle costs make it ideal for product‑embedded analytics.

## Strategic Focus
- **Agentic Analytics**: Deepening AI integration (MCP, Dives, Flights) to make MotherDuck the default data layer for AI agents and natural‑language querying.
- **Customer‑Facing Analytics**: Helping SaaS vendors embed isolated, fast analytics into their own products.
- **Cost Migrations**: Continuing to win customers leaving expensive cloud warehouses (Snowflake, BigQuery, Redshift) by delivering comparable power at a fraction of the cost.
- **Ecosystem Expansion**: Growing the 70+ partner integrations to cover more data ingestion, transformation, BI, and AI tools.

## Why Work Here
- **Culture & Values**: A globally distributed team (Stretch from Seattle to Amsterdam) that values collaboration, fun (“quacking together”), and building a product that redefines data analytics. Emphasizes creativity, entrepreneurship, and building the future of data.
- **Work Policy**: Remote‑first with physical hubs in Seattle, San Francisco, New York, and Amsterdam. Teams hold regular offsites.
- **Benefits** (from careers page): Competitive compensation and stock options; 100% paid medical, dental, and vision for employees (85% for dependents); flexible time away; 401k plan.
- **Engineering Culture**: Small, high‑impact teams; ownership from day one; opportunities to work on core database technology, cloud infrastructure, and AI integration. Engineers come from Google, AWS, Databricks, Snowflake, and DuckLabs.
- **Open Roles**: 11 active positions as of mid‑2026, including Backend Engineer (Amsterdam, Seattle, SF, NYC), Customer Engineer, Implementation Solutions Engineer, Account Executive, and Business Development Representative. Salary bands: $140K–$260K for engineering roles + equity; sales roles $100K–$260K + commission.

## Sources
1. [motherduck.com (Product Overview)](https://motherduck.com/)
2. [motherduck.com (About Us)](https://motherduck.com/about-us/)
3. [motherduck.com (Careers)](https://motherduck.com/careers/)
4. [linkedin.com (Company Profile)](https://www.linkedin.com/company/motherduck)
5. [builtin.com (Workplace Perception)](https://builtin.com/company/motherduck/faq/workplace-perception)

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