Platform Engineer

*This is a full-time, direct-hire opportunity. This is a remote/hybrid role (will need to come onsite to Round Rock, TX as needed) and candidates must be within 50 miles of Round Rock. 

Position Overview
We are seeking a Senior Platform Engineer to design and build the backend services and data-platform components supporting advanced, data-intensive systems. This is a hands-on software and product development position, not a traditional infrastructure operations role. You will translate an established architecture and data model into reliable production services that ingest, process, store, and export high-volume telemetry and derived data. The platform will span object storage, relational databases, distributed processing, and data-lake technologies while supporting both connected and disconnected environments. This position will have significant influence over engineering standards, technical tradeoffs, and product delivery. You will also provide technical leadership and mentorship as the engineering team grows.

Key Responsibilities

• Develop and implement core backend and data-platform services.
• Create stable, versioned service and API contracts using Protobuf and gRPC.
• Design and maintain relational database schemas for data management and application state.
• Build and optimize ingestion workflows for high-volume, unstructured time-series and telemetry data.
• Develop horizontally scalable asynchronous workers and distributed job-processing systems.
• Implement secure data upload, download, and object-management workflows.
• Establish automated unit, integration, contract, load, and failure-mode testing.
• Support troubleshooting, quality assurance, incident response, and production reliability.
• Implement platform observability through centralized logging, metrics, dashboards, alerting, and user-facing job-status information.
• Package, deploy, and operate cloud-native, containerized services.
• Collaborate with frontend, machine learning, product, and infrastructure teams.
• Document APIs, data contracts, deployment procedures, and operational runbooks.
• Conduct code reviews, mentor engineers, and help establish implementation standards.
• Ensure platform services meet applicable security requirements, industry standards, and organizational policies.

Required Qualifications

• At least five years of professional software engineering experience building and operating production backend, platform, data, or distributed systems.
• Strong proficiency in at least one production backend programming language; Go or Python is strongly preferred.
• Experience designing distributed services and asynchronous job-processing systems, including concurrency, retries, idempotency, failure recovery, and horizontal scaling.
• Experience developing production APIs with Protobuf and gRPC, including versioning, compatibility, authentication, and authorization.
• Strong relational database experience, including data modeling, schema migrations, referential integrity, query design, indexing, and performance tuning.
• Experience working with S3-compatible object storage and large-scale analytical, lakehouse, ETL, or time-series data systems.
• Experience packaging, deploying, and operating containerized applications using Docker, Kubernetes, Helm, and automated CI/CD workflows.
• Practical knowledge of production security and reliability practices, including IAM, RBAC, secrets management, access controls, audit logging, observability, automated testing, and incident troubleshooting.
• Ability to translate architecture and product requirements into incremental implementation plans, production-quality code, and clear technical documentation.
• Strong communication and collaboration skills, with the ability to work independently while providing technical leadership and mentorship.
• High school diploma or equivalent.
• U.S. citizenship and eligibility to obtain a U.S. security clearance are required.

Preferred Qualifications

• Experience with Apache Iceberg, Parquet, Apache Arrow, or similar lakehouse and columnar-data technologies.
• Experience with distributed messaging or workflow technologies such as Kafka, NATS, RabbitMQ, or MQTT.
• Experience with high-throughput data-processing frameworks such as Spark, Flink, or Beam.
• Experience processing high-volume telemetry, geospatial information, scientific time-series data, or other large unstructured datasets.
• Experience deploying systems in on-premises, private-cloud, disconnected, or air-gapped environments.
• Experience with infrastructure-as-code practices.
• Experience building data platforms that support machine learning training, inference, or model-evaluation workflows.
• Bachelor’s or master’s degree in a field relevant to the position.

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