Staff Data Platform Engineer

OXIO; New York (NY); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Stock options

Healthcare

Flexible work

Team lunches

Travel opportunities

Diversity & inclusion

Job summary

OXIO, a leading telecom‑as‑a‑service platform, is seeking a Staff Data Platform Engineer to design, build, and scale a modern data platform powering real‑time and batch analytics. You will drive a North Star data architecture and governance across telecom, product intelligence, and financial reporting use cases.

You will lead data pipelines, implement streaming/batch processing with Spark, Airflow, and DBT, and provision scalable infra using Terraform and Kubernetes.

Qualifications

• 15+ years of software engineering with focus on data systems and platform architecture.
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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 Spark, Airflow, and DBT.
• Lead infrastructure provisioning using Terraform and Kubernetes, ensuring scalable and secure deployments.
• Evaluate and drive the migration to a North Star data architecture aligning capabilities with long-term business goals.
• Collaborate with cross-functional teams to define logging standards, data contracts, and consumption patterns.
• Drive governance, privacy compliance (GDPR, CCPA), and metadata management.
• Build APIs and data services to support real-time activation and client-facing data sharing.
• Participate in strategic architectural decisions and long-term data roadmap planning.
• Evangelize modern data Platform & engineering practices across the organization.
• Mentor junior engineers and contribute to hiring and team growth.

Skills

Data platform

Scala

Python

SQL

Kafka

Airflow

Terraform

AWS

Kubernetes

ML infra

Education

BSc in CS

MS in Data/ML

Tools

Spark

DBT

Databricks

Snowflake

Tableau

PowerBI

Job description

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 like Spark, Airflow, and DBT
• Lead infrastructure provisioning using Terraform and Kubernetes, ensuring scalable and secure deployments
• Evaluate and drive the migration to our North Star data architecture, aligning platform capabilities with long‑term business goals
• Collaborate with cross‑functional teams to define logging standards, data contracts, and consumption patterns
• Drive best practices in data governance, privacy compliance (GDPR, CCPA), and metadata management
• Build APIs and data services to support real‑time activation and client‑facing data sharing
• Participate in strategic architectural decisions and long‑term data roadmap planning
• Evangelize modern data Platform & engineering practices across the organization
• Mentor junior engineers and contribute to hiring and team growth

Required Qualifications

• 15+ years of experience in software engineering with a strong focus on data systems and platform architecture
• 10+ years of experience building data solutions using data lakehouse architectures and self‑serve data platforms that empower scalable analytics across teams
• 10+ years of hands‑on programming experience with Scala, Go, Python, and SQL, building robust, high‑performance data systems
• 5+ years of experience building scalable data solutions using Python, Spark, and Terraform
• Proven experience building serverless and scalable ML infrastructure to support large‑scale data processing, ideally in telecom or similarly high‑throughput environments
• Deep expertise in cloud‑native data stacks (AWS, Databricks, Snowflake, BigQuery, Synapse)
• Strong understanding of microservices architecture, event‑driven systems (Kafka), and container orchestration (Kubernetes)
• Experience building operational tools and defining best practices to improve operational efficiency and developer experience—including evaluating and adopting AI‑based tools for engineering productivity
• Experience with orchestration tools like Airflow or Prefect and transformation tools like DBT
• Proficient in building and scaling APIs (REST/gRPC) for data access and activation
• Familiarity with front‑end technologies and frameworks (e.g., React) is a plus
• Built distributed Kafka pub/sub model for data ingestion pipeline with queue workers deployed on AWS ECS
• Automated monitoring, disaster recovery, CI/CD supported with filebeat/cloudwatch serverless monitoring
• Hands‑on experience with data visualization and BI tools (Tableau, PowerBI, Cibe.dev)
• Strong grasp of data governance, compliance frameworks, and secure data sharing practices
• Experience applying AI/ML and LLMs to data products and predictive analytics
• Exceptional communication and leadership skills in fast‑paced environments

What We Offer

• Competitive salary and stock option incentive program
• Company paid healthcare
• Flexible work arrangements
• Company sponsored team‑lunches and company retreats
• International organization that enables you to work across boundaries, travel to different locations, and enjoy the dynamics of a rapidly growing startup
• A diverse and inclusive team.
• We welcome applicants from all backgrounds to apply regardless of race, ethnicity, age, disability status or other defining characteristics.

OXIO is committed to fostering a diverse, equitable, and inclusive workplace where all employees feel valued and empowered. We believe that diversity in all its forms drives innovation and creativity, and we strive to create an environment that reflects and celebrates the unique backgrounds, perspectives, and talents of our employees. We do not discriminate against any employee or applicant for employment based on race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable federal, state, or local law. We are dedicated to providing a work environment free from discrimination and harassment. We committed to ensuring that all qualified applicants have an equal opportunity to apply for job openings. If you need assistance or an accommodation due to a disability, please contact us at [e-mail] for more information.