Staff Data Engineer

November 5

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OXIO

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Telecommunications • SaaS • Fintech

OXIO is a telecom company offering a cloud-native, programmable Telecom-as-a-Service platform that empowers businesses to launch and manage their own mobile networks. The company's platform, BrandVNO, enables the creation of custom mobile connectivity services without telecom expertise, allowing organizations to integrate these services seamlessly into their existing operations. OXIO provides tools for business intelligence, subscriber management, and personalized customer experiences, targeting retail, fintech, and various enterprise sectors. The company's API-first approach facilitates rapid innovation, cost reduction, and enhanced customer engagement across multiple markets.

51 - 200 employees

📡 Telecommunications

☁️ SaaS

💳 Fintech

📋 Description

• Help build, maintain, and scale our data pipelines that bring together data from various internal and external systems into our data warehouse. • Partner with internal stakeholders to understand analysis needs and consumption patterns. • Partner with upstream engineering teams to enhance data logging patterns and best practices. • Participate in architectural decisions and help us plan for the company’s data needs as we scale. • Adopt and evangelize data engineering best practices for data processing, modeling, and lake/warehouse development. • Advise engineers and other cross-functional partners on how to most efficiently use our data tools. • Develop data solutions through hands-on coding.

🎯 Requirements

• 15+ years experience as a data engineer and/or analytics engineer building large scale data platforms and scalable data warehouses. • 10+ years of hands-on experience coding in Python, Spark, SQL for building and maintaining data pipelines. • 5+ years of experience working with AWS cloud, dbt and Snowflake, Databricks, BigQuery, Redshift or other data warehouses • Proficient with Dimensional Modeling (Star Schema, Kimball, Inmon) and Data Architecture concepts. • Advanced SQL skills (ease with window functions, defining UDFs) • Experience in implementing real-time and batch data pipelines with strict SLOs, and optimizing data storage and access patterns. • Proven track record of enhancing data reliability, discoverability, and observability. • Hands-on experience with data visualization and BI tools (Tableau, PowerBI, Cibe.dev) • Strong grasp of data governance, compliance frameworks, and secure data sharing • Has good understanding of working with storage layers like Hudi, Delta Lake or Iceberg • Demonstrated success in leading large-scale projects across teams and mentoring others in Data Engineering best practices. • 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.

🏖️ 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.