Our client, a multinational telecommunications technology company is growing their high impact NCI Automation Project. They are seeking an experienced Sr. Python Developer for a high impact project to implement NOC automation monitoring of their data center networks during night time activity for KPI's, network alerts etc. This role will require you to be onsite 4-days per week at the client's NOC in Frisco, TX.

You will design and implement the core processing engine responsible for anomaly detection, metric evaluation, and scheduled reporting. This role is critical for building the intelligence behind the automation. This hybrid role combines the responsibilities of a Senior Python Engineer and a Data Scientist, leading the design and implementation of the anomaly detection engine, metric evaluation logic, and automation workflows. You will be the technical lead for intelligent monitoring and reporting during night deployments.

Key Responsibilities:

- Lead the development of anomaly detection models using statistical and machine learning techniques.
- Build Python microservices for metric evaluation, log mining, and smart alerting.
- Develop Python microservices to evaluate KPIs and logs using thresholds and anomaly detection.
- Design and implement scheduled reporting using Airflow or Cron. Build scheduled reporting modules using Airflow or Cron.
- Automate data collection from Grafana, OneData, and log databases.
- Collaborate with Full Stack and Backend Engineers to integrate services into the monitoring platform.
- Own the architecture and logic for trend analysis, delta tracking, and early warning systems.
- Contribute to infrastructure automation and deployment workflows.
- Implement logic for smart alerting and historical event tracking.


If you would like to learn more, please reach out to Elite technical.

Required Skills

- Minimum of 7 years of experience Application Development
- Must be willing and comfortable taking an online Python coding assessment

Required Skills:

- Expert in Python, Pandas, NumPy, and Scikit-learn.
- Experience with time-series data and anomaly detection algorithms.
- Familiarity with Airflow, Flask/FastAPI, and logging frameworks.
- Knowledge of cloud storage (S3, PostgreSQL) and API integration.
- Strong debugging and performance optimization skills.