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Data Engineering Lead
2 weeks ago
Company Overview: Tenth Revolution Group is a rapidly growing SaaS company leveraging IoT technology to shape the future of the railway industry.
About the Role:
The Senior Data Engineer will be responsible for designing and maintaining scalable data pipelines for high-volume IoT data ingestion using streaming platforms, partnering with the data science team to support real-time data processing and AI/ML workflows on platforms like Databricks, optimizing time-series databases, such as TimescaleDB, for terabyte-scale datasets, ensuring seamless integration of IoT telemetry with the data platform, managing cloud infrastructure on Azure using Infrastructure as Code (IaC) tools like Terraform, and deploying solutions with Docker.
Key Responsibilities:
- Design and maintain scalable data pipelines for high-volume IoT data ingestion.
- Partner with the data science team to support real-time data processing and AI/ML workflows.
- Optimize time-series databases for terabyte-scale datasets.
- Ensure seamless integration of IoT telemetry with the data platform.
- Manage cloud infrastructure on Azure using IaC tools like Terraform.
- Deploy solutions with Docker.
- Monitor and optimize pipelines for performance, scalability, and cost-efficiency.
Requirements:
The ideal candidate will have a strong technical background, proactive problem-solving skills, and experience creating scalable, data-centric solutions. Key qualifications include:
- 5+ years of experience in data engineering, with a focus on high-volume data pipelines and real-time processing.
- Proficiency with event streaming platforms for large-scale data ingestion.
- Expertise in handling terabyte-scale datasets using time-series databases.
- Hands-on experience with Python, including writing production-level code for data processing and AI/ML model deployment.
- Experience building APIs to expose data pipelines, models, and insights.
- Strong knowledge of cloud infrastructure services, IaC tools like Terraform, and containerization with Docker.