Hybrid Staff Data Platform Engineer

Posted 2 months ago

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About the role

  • Lead design and development of a scalable data platform for OXIO’s telecom-as-a-service. Building robust APIs and data systems while maintaining best practices in data governance.

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

Requirements

  • 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.

Benefits

  • 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.

Job title

Staff Data Platform Engineer

Job type

Experience level

Lead

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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