Staff Data Engineer

OXIO is the world’s first telecom-as-a-service (TaaS) platform, democratizing telecom for brands and enterprises. They are seeking a talented and experienced Staff Data Engineer to build and maintain data pipelines, ensuring the organization has access to reliable data for informed decision-making and innovation.

Responsibilities:

• 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

Requirements:

• Have 7+ years experience building large scale data platforms
• Experience in Data Engineering, and/or Analytics Engineering, building scalable data warehouses
• Proficient with Dimensional Modeling (Star Schema, Kimball, Inmon) and Data architecture concepts, able to coach and influence others to up-level the craft of Data Engineering
• Fantastic collaboration and communication skills, demonstrated by successful large-scale projects spanning multiple teams
• Advanced SQL skills (ease with window functions, defining UDFs)
• Experienced with Python, Spark for building and maintaining data pipelines & ETL/ELT processes
• Experienced working with dbt and Snowflake, BigQuery, Redshift or other data warehouses
• Experience implementing real-time and batch data pipelines with tight SLOs and complex transformation requirements
• Develop data models, schemas and standards for event data
• Optimize data storage and access patterns for fast querying
• Improve data reliability, discoverability and observability
• Familiarity to Data Engineering tooling: ingesting, testing transformations, lineage, orchestration, publishing data, metric layers
• Familiarity with storage layers like Hudi, Delta Lake and Iceberg
• Aptitude for product analysis, dashboarding, and reporting
• Familiarity with infrastructure tooling such as Terraform/Pulumi and worked with Kubernetes
• proficiency with AWS cloud
• Experience building streaming applications or pipelines using async messaging services or distributed streaming platforms like Apache Kafka
• Knowledge of Airflow or some other orchestration tool
• Experience with Spark or PySpark
• Experience with event-driven architecture and streaming data processing frameworks like Kafka, Spark, Flink
• Experienced with time-series databases like Clickhouse, InfluxDB