About BYANAT

We are building a next-generation AI-powered platform designed for comprehensive observability of digital infrastructure, including mobile networks and data centers. By leveraging advanced analytics, automation, and real-time monitoring, we empower businesses to optimize performance, enhance reliability, and prevent failures before they happen.

Our platform delivers deep insights, anomaly detection, and predictive intelligence, enabling telecom operators, cloud providers, and enterprises to maintain seamless connectivity, operational efficiency, and infrastructure resilience in an increasingly complex digital landscape.

Role Overview

This role is exclusively for Omani nationals and requires candidates to be Omani citizens.

We are looking for a talented and experienced Data Infrastructure Engineer to join our team.
This role focuses on building, deploying, maintaining, and optimizing data and ML infrastructure that supports our data-driven operations and AI/ML systems. You will work across large-scale data processing systems and production environments, ensuring they are robust, scalable, automated, and highly reliable.

The ideal candidate combines strong technical skills in distributed data systems with DevOps expertise, including CI/CD, cloud infrastructure management, and MLOps practices.

Key Responsibilities

• Design, develop, and maintain scalable data infrastructure solutions to support large-scale data processing and analytics.
• Deploy and configure distributed data systems, including data storage (e.g., HDFS, cloud storage) and data processing frameworks (e.g., Hadoop, Spark), ensuring they are resilient, optimized, and production-ready.
• Build and automate ETL workflows, managing data extraction, transformation, and loading processes to ensure data quality, consistency, and availability.
• Implement and manage CI/CD pipelines for data pipelines, services, and machine learning models in production environments.
• Automate infrastructure provisioning and deployment using Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible).
• Implement robust monitoring, logging, and alerting solutions (e.g., Prometheus, Grafana, ELK) to ensure system health and performance visibility.
• Collaborate with data scientists and ML engineers to operationalize machine learning models and maintain their reliability in production (MLOps practices).
• Monitor the health and performance of data infrastructure, troubleshoot and resolve production issues proactively.
• Optimize infrastructure scalability and resource efficiency using containerization and orchestration tools (e.g., Docker, Kubernetes).
• Establish best practices for data governance, security, compliance, and DevOps workflows tailored for data and ML systems.
• Stay updated on the latest trends and technologies in cloud infrastructure, big data, and machine learning operations.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 2+ years of experience building, deploying, and managing scalable data infrastructure.
• Strong experience with distributed big data technologies such as Hadoop, Spark, Hive, etc.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with cloud platforms (Google Cloud, AWS, Azure) and cloud-native architectures.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Knowledge of ETL pipeline orchestration tools (e.g., Apache Airflow, Luigi).
• Familiarity with CI/CD pipelines, infrastructure as code (Terraform, Ansible), and DevOps practices.
• Understanding of MLOps principles and experience operationalizing ML models (preferred).
• Knowledge of data formats like Parquet, Avro, ORC, and data querying using HiveQL or SQL.

Bonus Qualifications

• Certification in Big Data technologies (e.g., Google Cloud Professional Data Engineer).
• Experience with streaming data tools such as Apache Kafka, NiFi, or Flume.
• Telecom industry experience, particularly around network performance or customer analytics.
• Familiarity with observability tools (Prometheus, Grafana, ELK Stack).

What We Offer

• Performance-Based Compensation: Rewards tied to personal and company performance.
• Shares and Equity: Employee Stock Option Plan (ESOP) available.
• Growth Opportunities: Access to professional training and certifications.
• Comprehensive Benefits: Health insurance, pension contributions, and professional development support.
• Annual Vacation: Generous paid leave.
• Dynamic Work Environment: A culture of innovation, autonomy, and impact.
• Flexible Work Arrangements: Remote or office-based work options.
• A Mission-Driven Team: Join a passionate team shaping the future of digital infrastructure.