Staff Data Engineer

OXIO

Senior Data Engineer responsible for ensuring data-driven decision-making in a telecom-as-a-service platform. Collaborating with various teams to design and execute a robust data strategy.

Posted 6/16/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSBigQueryCloudETLKafkaKubernetesPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

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

What you’ll need

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
Nice to haves:
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.

Benefits

Comp & perks

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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data EngineeringAnalytics EngineeringDimensional ModelingSQLPythonSparkETLdbtSnowflakeBigQuery

Soft Skills

collaborationcommunicationcoachinginfluencing