About VideoAmp

VideoAmp is the tech-first measurement company transforming how advertising is valued, bought, and sold. Powered by currency-grade big data and a best-in-class technology stack, our platform gives advertisers, agencies, and digital partners the ability to plan, optimize, and measure media investments across every screen, from linear TV and OTT to CTV and digital video.

VideoAmp is accelerating investment in agentic AI and intelligent optimization technologies, helping clients drive measurable, real-world outcomes in an increasingly complex media landscape. With 880% year-over-year measurement growth, 98% coverage of the TV ecosystem, and partnerships with 11 agency groups and 1,000+ advertisers, were not just keeping pace with the industry. Were defining what comes next.

We believe great work requires great people, people who say Ill find a way instead of it cant be done.

The Role

The Principal Database Infrastructure Engineer will serve as a technical cornerstone of VideoAmps Database Infrastructure team, driving the design and execution of scalable, production-critical data systems that power VideoAmps platform. This is a high-impact individual contributor role at the intersection of distributed database engineering, query performance, storage architecture, and developer enablement.

You will architect and own the foundational database systems serving live customers and internal teams, operate in a rigorous, reliability-driven culture, and help VideoAmp scale its data infrastructure as the platform grows.

What Youll Do

• Design and implement the physical plan distribution pass, including network shuffle, coalesce, and partition isolator insertion. Own the plan serialization codec that ships sub-plans to workers, and maintain the S3 and Flight result exchange paths.

• Own worker discovery and heartbeating, and lead development of the next generation of load balancing: a work-stealing protocol and a replication-aware hash ring, both currently in design, to keep workers evenly loaded and resilient to node loss.

• Work across cost-based join reordering, cross-stage bloom filter cascade, scan deduplication, and selectivity estimation. Several of these live in our DataFusion fork; you will upstream where it makes sense and maintain the delta where it does not.

• Own the NVMe LRU cache over S3, Parquet read strategies including full-file and range reads, and Iceberg partition pruning and snapshot handling.

• Close the remaining gap on queries where we still trail Snowflake, specifically multi-shuffle plans and redistribution after scalar-subquery extraction. TPC-H benchmarks are the scorecard.

What Youll Bring

• 8+ years of software engineering experience with significant depth in database infrastructure, distributed systems, or data platform engineering.
• Strong systems programming in Rust, or deep C++ or Go experience with a clear path to Rust, including async runtimes such as Tokio and concurrent data structures.
• Proven experience building or significantly modifying a distributed data system such as a query engine, stream processor, distributed database, or large-scale data pipeline, with a solid understanding of shuffles, partitioning, and network and memory bottlenecks.
• Fluency with columnar formats and vectorized execution, including Arrow, Parquet, and the mechanics behind their performance characteristics.
• Strong grounding in distributed systems fundamentals: consistent hashing, leader and heartbeat protocols, backpressure, partial failure, and graceful degradation.
• A performance engineering mindset: you profile before optimizing and defend changes with real benchmark numbers.

• Direct experience with Apache DataFusion or another SQL query planner or optimizer such as Spark Catalyst, Calcite, Trino, ClickHouse, or DuckDB.
• Experience with Apache Iceberg or a comparable open table format such as Delta Lake or Hudi.
• Familiarity with Kubernetes and cloud infrastructure including EKS, S3, and IRSA, particularly on ARM or Graviton.
• Query optimizer experience including join ordering, predicate pushdown, and cardinality or selectivity estimation.

• Experience with a distributed SQL store such as CockroachDB, Flight SQL or gRPC, or contributions to open source data infrastructure projects.
• Experience building or working with developer tooling in agentic or programmatic data access contexts, and is a strong plus.

Compensation & Benefits

Our Values