Staff Data Engineer

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OXIO

Site WebLinkedInTous les Emplois

51 - 200 employés

📡 Télécommunications

☁️ SaaS

💳 Fintech

Telecommunications • SaaS • Fintech

OXIO est une plateforme cloud-native de télécommunications en tant que service qui permet aux entreprises de créer, gérer et personnaliser leurs propres réseaux mobiles sans la complexité généralement associée aux télécommunications. Offrant des solutions pour les Opérateurs de Réseaux Mobiles Virtuels (MVNO), les détaillants, les entreprises fintech et plus encore, OXIO permet aux utilisateurs d'intégrer une connectivité en temps réel dans leurs processus métier existants tout en tirant parti des analyses avancées par l'IA pour améliorer l'engagement client. L'approche API-first de la plateforme facilite l'innovation rapide, permettant aux entreprises de lancer des plans et services uniques à travers plusieurs réseaux dans le monde entier.

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.

🎯 Exigences

• 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.

🏖️ Avantages

• 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.