- Set the technical direction for Lytx's cloud data warehouse and lakehouse platform, balancing performance, cost, and reliability at scale.

- Design data models, pipelines, and storage layers that support analytics, reporting, and machine learning across the business.

- Partner with data engineering, analytics, product, and AI teams to translate business needs into platform capabilities.

- Lead complex, cross-team technical initiatives from design through delivery, and represent the data platform in architecture reviews.

- Improve data quality, governance, and observability so teams can trust the data they build on.

- Raise the bar on engineering practices through code review, design documents, and mentorship of engineers at all levels.

- Evaluate and introduce current tools and approaches where they solve a real problem, not for their own sake.

- Support the platform's ability to scale with Lytx's data volumes, including new data from AI safety features.

What We're Looking For

- 10+ years of experience in data engineering, with a track record of designing and operating large-scale data warehouse or lakehouse platforms in production.

- Deep hands-on experience with a modern cloud data warehouse (e.g., Snowflake, BigQuery, or Redshift) and distributed data processing (e.g., Spark).

- Strong SQL and Python skills, and experience building and maintaining data transformation pipelines (e.g., dbt, Airflow,



or similar orchestration tools).

- Solid understanding of data modeling, warehouse design patterns, and the tradeoffs between batch and streaming architectures.

- Experience operating data infrastructure on a major cloud provider (AWS, Azure, or GCP).

- A history of leading technical projects across teams and influencing architecture decisions without direct authority.

- Clear written and verbal communication — you can explain a complex data model to both an engineer and a business stakeholder.

- A bias toward pragmatic solutions: you know when to build for scale and when to keep things simple.

Nice to Have

- Experience with streaming data platforms (e.g., Kafka, Kinesis, or Flink).

- Experience supporting machine learning or AI feature pipelines.

- Background in IoT, telematics, video, or another high-volume sensor data domain.

- Experience with data governance, lineage, or cataloging tools.

How We Work: DRIVE

Lytx's culture runs on DRIVE: Deliver for the Customer, Responsibility in Every Outcome, Innovate with Purpose, Velocity with Excellence, and Elevate Each Other. As a Staff Engineer, you'll model these values daily — owning outcomes end-to-end, questioning assumptions to find better solutions, moving quickly without cutting corners, and investing in the growth of the engineers around you.

📌 Staff Data Engineer (Bengaluru)
🏢 Lytx
📍 Bengaluru