Sr. Software Engineer- Attribution
UnityMountain View, CA, USAPosted 7 April 2026
Job Description
The opportunity Unity is building a robust, near real-time reporting platform that powers critical analytics and decision-making across our ecosystem. We are looking for a Staff Software Engineer to help architect and implement the distributed data systems that drive this platform at scale.
In this role, you’ll design and build high-throughput, low-latency data processing pipelines that power reporting used by internal teams and external customers. You’ll operate at the intersection of distributed systems, stream processing, and cloud-native infrastructure — ensuring correctness, reliability, and scalability in a high-volume production environment.
This is a high-impact role where engineering rigor, architectural clarity, and production ownership matter.
What you'll be doing
Own the end-to-end attribution pipeline: You will be a core engineer on the team responsible for getting attribution data right — from the moment a user interacts with an ad, to the signal landing accurately in our data warehouse and in the hands of our ML and Reporting teams. This means owning a portfolio of high-throughput, latency-sensitive services and streaming pipelines that operate at the center of Unity's mobile advertising infrastructure.
Build and operate real-time ad event processing: You will design, build, and operate the online services that receive ad interaction events from mobile SDKs and other partners, process terabytes of data at scale (e.g. enrichments, transformations, privacy) and signals to our external and internal partners in real time.
Lead our architectural modernization: A significant part of your work will be an active migration, replacing a legacy event-handling layer with a modern gRPC-based service. This is greenfield development within a production system, requiring careful design, with backfill and failover behavior, while preserving data accuracy throughout the cutover.
Low-latency data services using caches: You will improve the caching layer that serves data on every ad request within strict latency budgets, and own the persistence layer that links auction, fill, placement, and gamer identities together across the ad lifecycle.
Build and maintain critical ad serving infrastructure: You will build and own multiple services that back ad serving (e.g. negative targeting, block listing) within the team's entire service portfolio. You are responsible for logging, tracing, and authentication; building Kafka-backed caching framework; health check and readiness probe infrastructure; and Docker-based integrations.
Drive data health monitoring and quality: You will own real-time monitoring of data health, detecting anomalies, event delivery rates, and data quality signals as they happen. You will build and maintain the batch data pipeline jobs that produce daily datasets in BigQuerty.
Collaborate across ML, Reporting, and external partners: You will be the team that ML modeling, Reporting, and external partners rely on for timely and accurate signal reporting. When something goes wrong, you will lead the investigation and recovery.
What we're looking for
Strong foundation in distributed systems and systems design.
Hands-on experience building and operating large-scale data processing systems.
Deep understanding of streaming concepts:Exactly-once semantics,Watermarking and event-time processing,Stateful stream processing,Checkpointing and recovery,Backpressure handling
Production experience with frameworks such as Apache Flink, Spark, Kafka, or similar technologies.
Proficiency in Python, Java, or Scala.
Experience with workflow orchestration tools (e.g., Airflow) for stream and batch coordination.
Strong understanding of cloud-native architectures and distributed infrastructure (Kubernetes, containerization, cloud platforms).
Additional information
Relocation support is not available for this position
Work visa/immigration sponsorship is not available for this position
Benefits At Unity, we want our team ... (truncated, view full listing at source)
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