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Senior Data Engineer

About Us

At Tavus, we're building the human layer of AI. Our mission is to make human-AI interaction as natural as face-to-face interaction, enabling the human touch where it has been previously unscalable. We achieve this through pioneering research in multi-modal AI models for human perception and understanding, combined with state-of-the-art human avatar rendering and communication models. Our models power everything from text-to-video AI avatars to real-time conversational video experiences across industries like healthcare, recruiting, sales, education, and more. By enabling AI to see, hear, and communicate with human-like authenticity, we're creating the foundation for the next generation of AI employees, assistants, and companions.

We're a Series A company backed by top investors, including Sequoia, Y Combinator, and Scale VC. Join us in driving the future of human-AI interaction. Check it out for yourself 😎

The Role

Data is the foundation of everything we build. We’re looking for a Senior Data Engineer who goes beyond pipelines and cleaning datasets. You’ll own our entire data strategy, from sourcing and curating to structuring and optimizing, ensuring our models and products are powered by the highest-quality data possible. You’re a true master of your craft including data sourcing, formatting, labeling, cleaning, and making use of our internal data. 

Your Mission 🚀

  • Be a data visionary – You anticipate the data needs not just for today, but for the future. You know how to curate diverse, high-quality datasets to ensure AI models reach their full potential.

  • You should have a product minded approach, and clearly understand the bigger picture of our mission and the importance of data to that. You’re constantly thinking about what data is missing for our next phase of models

  • Influence AI model training – Your data work will directly impact AI model performance, efficiency, and inference accuracy. You will collaborate closely with ML engineers to optimize datasets for maximum AI effectiveness.

  • Own the data, end-to-end – from sourcing to structuring—so it’s clean, scalable, and actually useful.

  • Be a data hunter – Web scraping, third-party deals, unconventional sources—you’ll find, collect, and curate the best multimodal data (text, video, images) to power our models. Manage large-scale data procurement to ensure our models train on the highest quality information.

  • Master video data – AI-generated video has unique challenges, from proper classification and segmentation to structuring it for machine learning training. You will own this challenge and ensure that our video datasets are structured for AI success.

  • Optimize labeling & automation – You will own the data labeling process and build automated workflows to make cleaning, labeling, and structuring data as efficient as possible. Work closely with our data annotation teams to ensure high-quality labeled data for ML models.

  • Turn internal data into gold – Our own platform is a goldmine of insights—help us unlock and use it to drive smarter decisions and supercharge growth.

  • Speed + precision – Move fast, but don’t break data. Every pipeline, dataset, and workflow should be tight, efficient, and built to last.

What We’re Looking For 🔥

  • You don’t just maintain - you build. From zero to fully running pipelines, you make things happen. You can take charge of how we use internal data to make smarter decisions.

  • Extreme ownership - You own data strategy end-to-end, proactively solving what data we need, where to get it, and how to structure it for AI impact.

  • Strategic mindset – You think beyond pipelines—you anticipate data needs before they arise and help shape AI development at Tavus.

  • Previous work with LLMs, multimodal data, is a big plus. You know how to source, structure, and optimize data for real AI impact.

  • Automation expert – You know how to automate data cleaning, structuring, and labeling workflows for efficiency and scale.

  • ML-first mindset – You understand that better data = better models and structure datasets to maximize AI model accuracy.

  • Fast, but flawless. Speed matters, but so does accuracy. You balance both.

  • You don’t follow best practices—you create them. A lot of what we’re doing is new- you set the standard for how data should be done.

  • Technical expertise – You have strong experience with Python, SQL, and large-scale data processing tools.

 

Benefits

When you join Tavus, you’re joining a diverse and supportive team. Our work is driven by our people, and our success is shared by all. This position has a flexible work schedule, unlimited PTO, extremely competitive healthcare and gear stipends, as well as, of course, plenty of fun! At the end of the day, we want Tavus to be a place for you to learn, directly drive impact, and be with a team you love.

To learn more about our team culture, and benefits, check out our hiring page!

Tavus is growing fast, and we’d like you to grow with us!  Are you excited to get your hands dirty and join the human-AI revolution? Drop your resume and we’ll be in touch!

We are not looking for cultural fits, we are looking for culture creators. In fact, diversity is what drives our success – it’s at the core of how we hire, communicate, and work. We are inclusive to all and combine our diverse backgrounds, skill sets, and thinking to build the best experiences for our clients.

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Average salary estimate

$140000 / YEARLY (est.)
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$160000K

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What You Should Know About Senior Data Engineer, Tavus

At Tavus, we're on a mission to redefine human-AI interactions, and we're seeking a passionate Senior Data Engineer to join our team. This role is pivotal as data is the backbone of our innovative models. You won't just be managing data pipelines; you'll take ownership of our entire data strategy. From sourcing and curating high-quality datasets to optimizing their structure for our AI models, you’ll ensure that the data powering our products is nothing short of outstanding. Your expertise in web scraping and unconventional data sources will inspire our models to reach new heights. Engaging with ML engineers, you'll help maximize model performance through strategic data usage. Picture transforming internal data insights into actionable growth strategies and shaping the landscape of AI with your data-driven vision. Let's not just keep up with the pace of innovation; let’s set the standard for how data should be handled in this space. At Tavus, you will find a supportive team environment, flexible work schedules, and ample opportunities for growth. If you're excited about contributing to the next phase of human-AI interaction, we'd love for you to join us on this journey and help us lead the charge in this groundbreaking field!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Tavus
What are the main responsibilities of a Senior Data Engineer at Tavus?

The Senior Data Engineer at Tavus is responsible for owning the data strategy from sourcing to optimization. This includes curating high-quality datasets, working closely with ML engineers to enhance AI model training, managing large-scale data procurement, and ensuring data accuracy and efficiency.

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What skills are essential for a Senior Data Engineer role at Tavus?

Essential skills for the Senior Data Engineer position at Tavus include strong expertise in Python and SQL, experience with large-scale data processing tools, a deep understanding of data structure optimization, and prior experience with LLMs and multimodal data.

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How does the Senior Data Engineer contribute to AI model performance at Tavus?

The Senior Data Engineer at Tavus directly influences AI model performance by ensuring that data is clean, well-structured, and meets the needs of the models through collaboration with ML engineers and optimizing datasets for efficiency.

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What does the data strategy involve for a Senior Data Engineer at Tavus?

The data strategy involves anticipating future data needs, proactively sourcing diverse datasets, automating cleaning and structuring workflows, and leveraging internal insights to drive better decision-making within Tavus.

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What is the team culture like for a Senior Data Engineer at Tavus?

The team culture at Tavus is diverse and supportive, centered around collaboration and growth. As a Senior Data Engineer, you’ll work with a team that values inclusivity, encourages innovation, and strives to create impactful solutions in the human-AI interaction space.

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Common Interview Questions for Senior Data Engineer
Can you describe your experience with data cleaning and structuring at a previous job?

In your response, highlight specific tools or methodologies you used for data cleaning and structuring, focusing on examples where your work significantly impacted the data quality and model performance.

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How do you prioritize and manage multiple data sourcing projects?

Share your approach to project management, emphasizing the importance of setting clear goals, utilizing project management tools, and communicating effectively with colleagues to stay aligned.

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What strategies do you use to ensure data accuracy and integrity?

Discuss methods such as regular data audits, validation checks, and the implementation of automated testing processes to maintain high data integrity in your projects.

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How do you approach collaboration with machine learning engineers?

Emphasize the importance of open communication, sharing insights, and understanding each other's workflows to align on the best data solutions that will enhance model performance.

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What tools and technology do you prefer for data processing and why?

Reference specific tools you have experience with, explaining why you prefer them in your data processing workflows, and how they align with best practices in the field.

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Describe a time when you had to find a data source unexpectedly. What did you do?

Provide a detailed example of your resourcefulness in data sourcing, discussing the unconventional methods you used to successfully find and curate the needed data.

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How do you keep abreast of the latest trends and developments in data engineering?

Discuss resources such as webinars, industry conferences, technical blogs, and online courses that you utilize to stay updated on emerging tools and best practices in data engineering.

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What are some challenges you anticipate when working with multimodal data?

Identify potential challenges such as data inconsistencies, varying data formats, and the need for specialized preprocessing, and discuss your strategies for overcoming these obstacles.

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Can you explain the importance of automation in data workflows?

Discuss how automation enhances efficiency, reduces human error, and allows for scaling up operations, emphasizing its role in modern data engineering practices.

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What does a successful data strategy look like to you?

Share your vision for a successful data strategy, focusing on aspects such as alignment with business goals, scalability, quality assurance, and adaptability to technological advancements.

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Making personalized video messages scalable using AI

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DATE POSTED
April 11, 2025

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