> Markdown version of [/jobs/ext/3876295-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3876295-data-platform-engineer). 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). --- # Data Platform Engineer - **Company:** Washington and Idaho Railway Inc - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Data Control, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Data Structures, Monitoring of Systems, Python (Programming Language), Cloud Services, Snowflake, Apache Spark, Event Driven Architecture, Kubernetes, Data Lineage, Virtual Agents, Terraform, Data Pipelines - **Published:** October 22, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pthnnrlqx0 ## About the Role * Proven experience building loosely coupled production services, APIs, and SDKs in Python used by multiple teams. * Experience developing metadata-driven platforms that integrate with catalogs, lineage tracking, and automatic checks for contracts and data quality. * Strong background in building observability solutions that provide meaningful signals for monitoring and troubleshooting. * Excellent communication skills, with the ability to advocate for architecture standards and mentor team members. * Extensive experience with AWS cloud services, Terraform, and Kubernetes for scalable infrastructure deployment. * Familiarity with data governance, schema management, and automated data certification processes. * Understanding of data pipelines, particularly moving from batch to streaming architectures, and knowledge of cost tradeoffs involved. * Hands-on experience with Spark, Iceberg at scale, and Snowflake in a production environment. * Background in ad tech or domains with high-volume event data and multiple consumers. * Experience developing tooling and data structures suitable for AI agent operation is a plus. ## Description We are seeking a highly skilled and motivated founding engineer to join our Data Platform team. This pivotal role involves shaping the technical standards and building the foundational software that will enable and enforce data governance, quality, and accessibility across the entire organization. As a key contributor, you will work directly with the Senior Director of Data Engineering to develop a unified platform that allows advertisers to run campaigns seamlessly across CTV, web, mobile apps, and social media through a self-serve model. Your responsibilities will include designing and implementing a comprehensive data control plane, developing tools and libraries to streamline data product deployment, and establishing observability standards to ensure data reliability and quality. This role offers a unique opportunity to influence the future of Kargo's data infrastructure, grow a talented team, and drive innovation in data engineering practices that support automation, * Design and develop the data control plane to provide a centralized view and governance over data products, including schemas, lineage, ownership, and quality metrics. * Create standardized libraries, SDKs, templates, and CI/CD pipelines to facilitate the rapid and consistent deployment of data products across teams. * Implement enforcement layers such as schema registries, contract validators, and automated certification processes to uphold data standards. * Ensure all data products are observable by default, with metrics on freshness, volume, schema conformance, and quality integrated into existing monitoring systems. * Define and set the technical direction for the data platform, including architecture, roadmap, and strategic build versus buy decisions. * Lead design reviews and collaborate with cross-functional teams to ensure the platform remains modular, scalable, and aligned with organizational needs. * Grow and mentor the data platform team, fostering a culture of innovation, best practices, and continuous improvement. * Engage with stakeholders to understand their data needs and translate them into scalable, reliable solutions.