> Markdown version of [/jobs/ext/4622615-staff-software-engineer-feature-platform](https://www.wearedevelopers.com/jobs/ext/4622615-staff-software-engineer-feature-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer, Feature Platform

- **Company:** UNITY PARTNERS
- **Location:** Mountain View, CA, United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Cloud Computing, Extract Transform Load (ETL), Data Systems, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, SQL Databases, Data Streaming, Feature Store, Data Processing, Real Time Systems, Apache Spark, Parallel Computation, Backend, Kubernetes, Low Latency, Apache Flink, Machine Learning Operations, Stream Processing, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_f9608604346a9a94d6ae703dec115c99

## About the Role

* Strong software engineering fundamentals with deep experience designing and operating large-scale distributed systems in production
 * Hands-on experience building production-grade ETL/ELT pipelines using Python, Java, SQL, or similar technologies
 * Experience with distributed processing frameworks such as Spark or Flink in both batch and streaming modes, including performance tuning and parallel computation
 * Understanding of how offline data systems integrate with online serving layers - feature stores, low-latency APIs, and real-time systems
 * Experience with cloud-native environments, containerized systems, Kubernetes, and workflow orchestration tools
 * Strong ownership mindset - focused on correctness, observability, and long-term maintainability
 * Experience with Go is a plus, particularly for collaboration on high-throughput feature serving services, * Experience with ML infrastructure, feature stores, or model training pipelines
 * Background in ads, attribution, or monetization systems
 * Familiarity with experimentation and metrics infrastructure
 * Exposure to high-scale backend or platform engineering, This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

*Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.

## Description

This role goes beyond data processing. You'll own the full software lifecycle of pipeline systems - from architecture and implementation through to reliability, observability, and performance at scale - collaborating closely with ML, backend, and product teams to build durable, high-quality infrastructure that supports both offline training workflows and online feature serving., * Design, build, and operate scalable, production-grade data pipeline systems and curated feature datasets powering ads optimization and ML

 * Own end-to-end offline data flows from raw event ingestion to feature-ready datasets, with strong emphasis on correctness, reproducibility, and SLA compliance
 * Develop and maintain large-scale batch and streaming systems (Python / Java / SQL) with a strong focus on performance, cost-efficiency, and reliability
 * Build and contribute to our Feature Store platform, including integration with the high-throughput online serving layer (Go-based services)
 * Translate complex product and monetization logic into well-engineered, extensible systems serving analytics and machine learning use cases
 * Drive improvements in observability, testing frameworks, and quality standards across the platform
 * Lead architectural decisions and engineering best practices within the Feature Platform team