Staff Data Platform Engineer

🇺🇸 United States
$2K - $2K Annual
Posted 5 months ago
Expires May 29, 2026

STAFF DATA PLATFORM ENGINEER

OXIO is the world’s first telecom-as-a-service (TaaS) platform. We are democratizing telecom and making it easily accessible for brands and enterprises to fully own and operate proprietary mobile networks designed to support their own customers needs. Our TaaS solution combines multiple existing networks into one single platform that can be seamlessly managed in the cloud as a modern SaaS offering. And it gets better - with full network access comes unparalleled business intelligence and insights to help enterprises better understand customer and machine (M2M) behavior. With a continuous focus on innovation, any company can build a powerful telecom presence with OXIO, and in addition help them glean unique customer insights like never before.

Job Description:

We’re seeking a seasoned Staff Data Engineer to lead the design, development, and scaling of our modern data platform. This role is ideal for someone who thrives in building and designing robust data systems. You’ll be instrumental in shaping our data infrastructure, driving governance, and building scalable APIs that power real-time and batch analytics.

You will also play a pivotal role in evaluating, designing, and migrating our organization toward a North Star data architecture—a future-proof foundation that supports scalable, secure, and intelligent data operations across the enterprise.

This role supports a wide range of analytics use cases across telecom networking, product intelligence, financial reporting, and internal/external data insights. You’ll help build a comprehensive Customer 360 platform powered by ML models and behavioral data, enabling advanced use cases such as fraud detection, brand intelligence, and personalized customer engagement.

Key Responsibilities

- Architect, build, and scale a unified data platform integrating internal and external sources into data lakes and warehouses

- Design and implement streaming and batch data pipelines using tools...

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