About Turntable
What we do
Turntable (YC W23) enables less technical analysts to build their own data pipelines. Companies use our AI-native workspace to scale their analytics stack without hiring more engineers.
The founding team has experience building data and ML products at Stripe, Pinterest, Twitter, and Cruise. Justin led the commercial data science team at Cruise, Ian built ML and data tools at Pinterest and Stripe, and Wally led product for Twitter’s largest ML team, the Home Timeline.
At all of these companies, we encountered the same problem: data pipelines are too hard to build and maintain. Often business stakeholders who know SQL can unblock themselves if only the tooling was better.
Our vision
The jobs of the last million data professionals will look different than the next million. Data is more vital to an organization than ever before but the majority of data tools are still too complex and hard to use.
We combine modern data warehousing technology, large language models and a delightful user experience to craft a category defining product.
We believe that if we are successful in our mission, we will change how organizations use data to develop products, run daily operations and plan for the future.
About the role
Skills: Python, React, TypeScript, Data Warehousing, PostgreSQL, Amazon Web Services (AWS)- 📍 New York, NY or Remote
- 📊 Generous equity
- 🤝 4 person team
- ⏱️ Full-time
- 💰 $150K-$225K
- 🩺 Benefits (health, dental, vision, new equipment, etc)
💽 What we do
We’re on a mission to build the future of analytics infrastructure. Data teams use Turntable to build and maintain data pipelines that power every aspect of their organization from the finance department to operations.
The founding team has experience running data teams and building products at companies like Stripe, Pinterest, Twitter, Cruise, Reddit and Coinbase.
We’ve raised $3.2M from world-class investors.
🔮 Our vision
The jobs of the last million data professionals will look different than the next million. Data is more vital to an organization than ever before but the majority of data tools are still too complex and hard to use.
We combine modern data warehousing technology, AI and a delightful user experience to craft what we believe will be a category-defining product.
If we are successful in our mission, we will change how organizations use data to develop products, run daily operations and plan for the future.
👩💻 About the role
We are looking for a stellar full-stack engineer to join our engineering team. You’ll work directly with the co-founders and our early customers to help data teams around the world be more effective at working with their data.
This is a role that is strongly focused on product and you will often be designing new features from scratch that are brand new to the industry. Customer-facing product development experience is a big plus.
We offer competitive salary and equity as well as a slate of other benefits:
- Health insurance
- Dental insurance
- Vision insurance
- New equipment (new Macbooks, monitor, etc)
- Quarterly offsites
🏗️ Interesting Problems We are Solving
There is no shortage of interesting technical problems to solve in our space. We have years of work ahead of us and your time spent working with us will be on high-impact, customer-facing products.
Here’s a preview of some of the types of projects you can expect to work on:
- Developing AI models that can generate SQL, write documentation and understand an organization’s data models in their warehouse
- Hacking up SQL compilers, network libraries and abstract syntax tree parsers to generate a column-level data lineage view of an entire data warehouse
- Building large canvas, Figma-like frontend experiences
- Architecting large scale workflow systems
- Designing realtime, multiplayer infrastructure
🛠️ Our Engineering Culture
At Turntable, we take inspiration from how some of the best engineering teams in the industry operate. We don’t shy away from adding in our own remixes as well.
Some examples of how we work
- We dogfood our own product every day. We build data pipelines for our business in Turntable and we often hop into our product to help customers be successful.
- We prioritize speed and rapid iteration. We believe that done is better than perfect and that most of the learning of a feature happens after launch.
- We are low ego and high empathy. We believe good software is not enough to build a category-defining product - we also need a highly functional team.
- We all wear the customer hat. Engineers at Turntable will often interact with customers and the customer are at the center of what we build.
- We celebrate wins, ships, and learnings. We host Friday happy hours to demo what was built during the week and to share what we learned.
- Slope > intercept. We believe a good engineering culture should be focused on providing interesting opportunities to engineers to grow and level up their careers.
💻 Our Tech stack
Our tech stack is always evolving. We don’t expect candidates be an expert at every part of our stack. Here are the highlights:
Artificial Intelligence
- Pytorch
- The OpenAI platform
- PGvector
- Local model development (ex: llama2)
- New LLM patterns (ex: fine-tuning, retrieval augmented operation (RAGs)
Backend
- Python
- dbt-core
- Fastapi
- Docker
- Postgres
- AWS
Frontend
- React
- Typescript
- Tailwindcss
- Vercel
Technology
Interesting Problems We are Solving
There is no shortage of interesting technical and product problems to solve at Turntable. We have years of development work ahead of us and your time spent working with us will be on high-impact, customer-facing product features.
- Developing AI models that can generate SQL, write documentation and understand an organization’s data models in their warehouse
- Hacking up SQL compilers, network libraries and abstract syntax tree parsers to generate a column-level data lineage view of an entire warehouse
- Building large canvas, Figma-like frontend experiences
- Designing realtime, multiplayer infrastructure
Our Tech stack
Our tech stack is always evolving. We don’t expect candidates be an expert at every part of our stack. Here are the highlights:
Artificial Intelligence
- Pytorch
- The OpenAI platform (fine tuning, gpt4, gpt3.5, embeddings)
- PGvector
Backend
- Python
- Fastapi
- Docker
- Postgres
- AWS
Frontend
- React
- Typescript
- Tailwindcss
- Vercel
