Principal Data Architect
Novi Sad,
Serbia
Our team is global, addressing the challenges of bringing safe ADAS and autonomous automotive systems to market for our customers.
As a Principal Data Architect, you will be the primary visionary for our global data strategy. You will tackle the "unsolved" problems of autonomous vehicle data: how to efficiently store, index, and query petabytes of high-dimensional, multi-modal sensor data.
You will lead the transition of our data infrastructure into a state-of-the-art Open Lakehouse architecture, leveraging Apache Iceberg and the Hadoop ecosystem to create a deterministic, high-performance environment for ML research and safety-critical validation.
This role would require you to work for two years in our Serbian office, with the option of then moving to the US office.
Responsibilities
- Lead the design of a data lakehouse that supports the requirements of ADAS/AV, including 4D spatial-temporal querying and multi-modal data fusion.
- Develop custom partitioning schemes, Z-ordering, and hidden indexing strategies tailored for LiDAR, radar, and video metadata.
- Solve challenges regarding data consistency, deterministic "replay" of vehicle logs, and massive-scale data lineage
- Develop algorithms for data deduplication and "intelligent tiering," ensuring that rare "edge-case" driving data is preserved while optimizing the cost-to-performance ratio of the petabyte-scale lake.
- Partner with ML teams to ensure the data architecture supports emerging paradigms like Foundation Models and End-to-End Autonomous Driving architectures.
Must Have
- PhD in Computer Science, Distributed Systems, Database Systems, or a related quantitative field.
- 5+ years of experience in data systems, with a significant track record of designing large-scale distributed architectures.
- Deep, "under-the-hood" knowledge of Apache Iceberg (specification and implementation) and the Hadoop ecosystem (HDFS, Spark, Trino/Presto).
- Evidence of contributions to the field, such as publications in top-tier conferences (e.g., SIGMOD, VLDB, ICDE, OSDI) or a history of significant contributions to major open-source data projects.
- Expert-level understanding of query optimization, file format internals (Parquet/Avro), and the trade-offs of distributed consensus protocols.
Nice to have
- Automotive Safety Standards: Understanding of data integrity requirements for ISO 26262 or SOTIF (Safety of the Intended Functionality).
- Geospatial Mastery: Experience with H3, S2, or other spatial indexing systems for high-frequency GPS and trajectory data.
- Cloud Economics: Proven ability to manage the financial architecture of massive cloud deployments (AWS/Azure/GCP).
What's great in the job?
- Great team of smart people, in a friendly and open culture
- No dumb managers, no stupid tools to use, no rigid working hours
- No waste of time in enterprise processes, real responsibilities and autonomy
- Expand your knowledge of various business industries
- Create content that will help our users on a daily basis
- Real responsibilities and challenges in a fast evolving company
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