---
title: 'Marketing Operations Manager at LanceDB'
canonical: 'https://feeny.ai/job/marketing-operations-manager-lancedb-united-states-canada-gp9dz49pczn3'
type: 'job'
last_seen: '2026-10-18'
---

# Marketing Operations Manager at LanceDB

- **Company:** LanceDB
- **Location:** United States / Canada
- **Compensation:** $160k–$190k
- **Employment:** full-time
- **Posted:** 2026-10-13
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.ashbyhq.com/lancedb/89585d0c-019a-4ac2-ab2c-812f8ea306ca

## Job description

## About LanceDB

AI advances at the speed of its research, and research moves at the speed of its data. LanceDB is the AI-native Multimodal Lakehouse: one system where a researcher curates petabytes of video, audio, and every signal derived from them with a few lines of Python, and the next training run starts as fast as the next idea. Customers like Runway, Midjourney, and Netflix build the future of AI on LanceDB, from frontier and world models to robots and autonomous vehicles.

## About the Role

We're looking for a Senior Marketing Operations Manager to build the systems that turn LanceDB's marketing into measurable pipeline. Your job is to own the marketing tech stack, the data flowing through it, and the reporting that tells us what's working and what isn't.

You'll partner closely with our Head of RevOps, who owns the sales side of the CRM and the revenue process. Your domain is everything Marketing touches on the way to a qualified opportunity: lead capture, inbound lead routing, scoring, attribution, campaign and event operations, and the reporting that proves Marketing's impact on revenue.

One of the biggest opportunities in front of you is our open source. LanceDB sees millions of open source downloads per month, but we’re still early in our journey to reliably monetizing the open source funnel. You'll build the open-source qualified lead program that turns product and community signals into real sales outreach at the right now.

This is a 0-to-1 builder's role on a small, fast-moving team. You won't inherit a mature ops function. You'll design it, implement it, and keep it running as our go-to-market motion evolves.

## What You'll Do

- Be the directly responsible individual (DRI) for our marketing systems, including HubSpot marketing automation, signal and enrichment tools (e.g. Common Room, Clay), advertising platforms (Google Ads, LinkedIn, Reddit), web analytics, and event and webinar tooling. You’ll help audit what we have, decide what we need, and implement (or cut) systems when necessary.
- Build and run lead management: capture, enrichment, account assignment, routing, lifecycle stages, and scoring, so the right leads reach the right sellers quickly and nothing falls through the cracks.
- Own event lead flow end to end, including registration, badge scans, enrichment, account assignment, and follow-up routed to the right owner within a clear SLA.
- Build and run the open-source qualified lead program with Product, Engineering, and Marketing, turning open-source activity and account behavior into a scoring system that triggers outreach at the right moment.
- Contribute to attribution and marketing reporting. Build the dashboards that show sourced and influenced pipeline by channel, program, and account, including a practical way to measure influence on founder-led and frontier lab deals that Marketing shapes but doesn't source.
- Keep our data clean. Own marketing data hygiene, field governance (including Deal Source), deduplication, and enrichment in partnership with RevOps.
- Run campaign operations: forms, landing pages, email programs, list uploads, and registration flows, including for flagship events like our Reverie summit.
- Support the operating rhythm for Marketing: weekly funnel reporting against goal (MQLs, meetings booked and held, pipeline, and new ARR), budget tracking, and the data to support quarterly planning.
- Partner with Revenue Marketing on ABM infrastructure, including target account lists, segmentation, intent and engagement signals, and program measurement.
- Proactively find and ship improvements. Use AI and automation to make the whole team faster, from enrichment and research workflows to reporting.

## What We're Looking For

- You thrive in a fast-paced, startup environment and enjoy working with high-caliber teams.
- 6-8 years in marketing operations, revenue operations, or growth operations at B2B technology companies, ideally related to developers or AI.
- Someone who is AI-pilled. In addition to having a MOPs background, you’re comfortable with a GTM engineering approach and using the latest AI tools like Claude or Codex to build in intelligent automations.
- Deep, hands-on experience with a CRM (SFDC or HubSpot) with a focus on marketing automation, workflows, lifecycle, reporting, and data modeling. You've built these systems yourself, not just managed an agency or team that did.
- Experience with the modern GTM data stack, such as enrichment and workflow tools (e.g. Clay), signal platforms (e.g. Common Room), sales engagement (e.g. Apollo), ad platforms, and web analytics.
- Hands-on experience designing lead routing and account assignment, including assigning event lead flow.
- A track record of building attribution and pipeline reporting that leadership trusts and uses to make decisions.
- Experience with PLG, open-source, or product-usage signals feeding a sales-led motion is a strong plus.
- Proven ability to own work end to end without a team to support you. You have taste and strong pattern-matching for common problems, and you move quickly and with confidence.
- A foundation-builder's mindset: you're motivated by creating process, systems, and measurement where little exists today, and you know when "good enough and shipped" beats "perfect and pending."
- You use AI thoughtfully as an operator, iterating on how it can improve and streamline your work and the team's.
- Excellent communicator who can partner with founders, Sales, RevOps, and Engineering and move fast in a small, high-ownership team.
- Bonus points for: experience at an AI, database, data infrastructure, or developer tools company, or scripting and API experience (Python, webhooks, reverse ETL).

## About LanceDB

## Core Business
- **Primary industry**: AI data infrastructure / vector databases / multimodal lakehouse
- **Target customers**: B2B – AI/ML teams, enterprises building generative AI, recommendation systems, and large-scale training pipelines.
- **Mission/purpose statement**: “Build Better Models, Faster” by providing a unified foundation to accelerate training dataset development.

## Products & Services
- **Embedded Vector Database**: Open-source vector database for multimodal AI, scaling to billions of embeddings with minimal management. Supports vector/semantic, full-text, and hybrid search combined with SQL filters.
- **Multimodal Lakehouse (LanceDB Enterprise)**: A unified platform for curation, feature engineering, retrieval, and training at massive scale. Includes automated pre-processing, versioning, branching, and rollback.
- **LanceDB Cloud**: Managed cloud service with auto re-indexing, caching, and a management dashboard – no server management required.
- **Lance Format**: A modern columnar data format optimized for AI training, analytics, and retrieval – significantly faster than Parquet and WebDataset.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding $41.1M; annual revenue $1.2M (LinkedIn estimate)
- **Notable Investors/Partners**: Theory Ventures (led Series A), CRV, Swift Ventures, Y Combinator.
- **Growth Signals**:
  - Headcount: 32 employees (+135% YoY, +9.3% monthly growth)
  - Customers include Midjourney, Runway (testimonials on lancedb.com)
  - 11,382 LinkedIn followers (+60.1% yearly)
  - 6 active job postings; monthly job posting trend +20%

## Competitive Advantages
- **Open-source core** with a permissive license, enabling community adoption and vendor lock-in avoidance.
- **Lance columnar format** – purpose-built for AI workloads, offering fast random access, column appends without rewriting, and 70% Model FLOPS Utilization (MFU) during training.
- **Multimodal by design** – stores vectors, images, tensors, video, and metadata in a single table, replacing 3–4 different data stores.
- **SSD-based ANN index** – scales beyond memory for low-latency billion-scale vector search on a single node.

## Strategic Focus
- Accelerate development of the Multimodal Lakehouse (announced with Series A)
- Expand enterprise features (managed cloud, security, compliance)
- Grow ecosystem integrations (Spark, Python UDFs, etc.)
- Scale go-to-market and customer success (hiring Forward Deployed Engineers, Solutions Engineers)

## Why Work Here
- **Culture**: Startup environment with deep open-source roots; founders are former pandas co-author (Chang She) and HDFS/core contributor (Lei Xu). Engineering-heavy team (38% technical).
- **Remote/hybrid policy**: Not explicitly stated; likely flexible given distributed team (US, Canada, China) and startup nature.
- **Notable perks/engineering culture**: Work on foundational AI infrastructure used by Midjourney and Runway. Opportunities to contribute to open-source, build in Rust, and shape the multimodal data ecosystem. Fast-growing company with strong investor backing.

## Sources
1. [lancedb.com](https://www.lancedb.com/)
2. [crunchbase.com](https://www.crunchbase.com/organization/lancedb)
3. [linkedin.com](https://www.linkedin.com/company/lancedb)
4. [ycombinator.com](https://www.ycombinator.com/companies/lancedb)
5. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/lancedb)

## Other roles at LanceDB

- [Senior Software Engineer](https://feeny.ai/job/senior-software-engineer-lancedb-americas-apac-3z7keg1bwak1) — Americas / APAC
- [Senior System Test Engineer](https://feeny.ai/job/senior-system-test-engineer-lancedb-united-states-canada-as5kbb9zexxh) — United States / Canada
- [Documentation Engineer](https://feeny.ai/job/documentation-engineer-lancedb-united-states-canada-f28jc38958g5) — United States / Canada
- [Senior Solutions Engineer](https://feeny.ai/job/senior-solutions-engineer-lancedb-san-francisco-0btn7w423bah) — San Francisco, CA
- [AI Research Engineer](https://feeny.ai/job/ai-research-engineer-lancedb-united-states-kzr7s7kn5xsw) — United States
- [Senior Product Manager](https://feeny.ai/job/senior-product-manager-lancedb-united-states-canada-kddh90xzsr7s) — United States / Canada
- [Controller](https://feeny.ai/job/controller-lancedb-united-states-6rafknnjaa3f) — United States
- [Senior Product Security Engineer](https://feeny.ai/job/senior-product-security-engineer-lancedb-united-states-canada-0b3xt2p24427) — United States / Canada
- [Founding Revenue Marketer](https://feeny.ai/job/founding-revenue-marketer-lancedb-united-states-canada-mcb1thtdv07v) — United States / Canada
- [Senior Customer Success Engineer](https://feeny.ai/job/senior-customer-success-engineer-lancedb-united-states-canada-2vht5p4k14na) — United States / Canada