Principal Data Engineer

Overview

Sanas is revolutionizing the way we communicate with the world’s first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard.

Sanas is a 200-strong team, established in 2020. In this short span, we’ve successfully secured over $100 million in funding. Our innovation has been supported by the industry’s leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you’re not just adopting a product; you’re investing in the future of communication.

Role

We’re looking for an experienced and forward-thinking Principal Data Engineer to lead the design and implementation of our end-to-end data infrastructure for industry-leading Voice AI products. This is a high-impact role where you will shape the technical vision, own strategic architecture decisions, and mentor a growing team of Data engineers focused on delivering reliable and scalable data systems for Machine Learning at scale.

You’ll work cross-functionally with AI research scientists, infrastructure and product teams to ensure that data—from raw audio to training-ready features—is consistently accessible, compliant and optimized for speed and scale. You’ll help push the boundaries of real-time Voice AI!

Key Responsibilities

• Architect and lead the development of large-scale data pipelines and data lakes to ingest, transform and serve high-quality data for AI model training, product telemetry and analytics.
• Drive long-term data infrastructure strategy across streaming and batch, feature store extensions, Iceberg / Delta lake choices, metadata management, and lakehouse evolution.
• Drive platform and infrastructure decisions, optimizing compute fleets (e.g., Ray, Spark clusters), orchestration tooling (Airflow, Dagster), and streaming stacks (Kafka, Flink).
• Collaborate with AI research scientists, engineering leads, product, finance, marketing, and legal to align data architecture with business and regulatory requirements.
• Advocate best practices in data governance, lineage, observability, testing, tooling, and disaster recovery across pipelines and data stores.
• Act as a mentor and technical leader—review design and code, share patterns, elevate team capability, and support recruitment and hiring.
• Drive build vs buy decisions for tools to implement data quality and observability solutions to achieve high data quality.

Qualifications

Nice to Have

Joining us means contributing to the world’s first real-time speech understanding platform revolutionizing Contact Centers and Enterprises alike.

Our technology empowers agents, transforms customer experiences, and drives measurable growth. But this is just the beginning. You'll be part of a team exploring the vast potential of an increasingly sonic future.

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