Telecom Data Engineer

Cynet Systems - Dallas, TX

Full-time

Dallas, TX

Professional, Scientific, and Technical Services

About the position

The Telecom Data Engineer will be responsible for developing and deploying data solutions using Palantir Foundry, focusing on managing and processing large telecom datasets. This role involves designing data pipelines, implementing analytical solutions, and collaborating with cross-functional teams to enhance telecom applications and address industry-specific challenges.

Responsibilities

• Develop and deploy solutions in Palantir Foundry.
• Design, build, and deploy data pipelines, workflows, and custom applications using Palantir Foundry.
• Create data integration, data transformation, and ETL solutions to manage and process large telecom datasets.
• Implement analytical solutions, reports, and dashboards tailored to telecom-specific use cases.
• Analyze complex telecom datasets to identify patterns, trends, and actionable insights.
• Design and implement data models that accurately reflect telecom network data, usage, and customer behavior.
• Collaborate with data scientists to support machine learning model deployment within Foundry.
• Leverage telecom expertise to ensure data solutions align with industry standards and regulatory requirements.
• Develop data applications that address telecom challenges like demand forecasts, Core Network Planning and Design, and Core Network Delivery and Assurance.
• Contribute to projects focused on wireline, wireless, network performance, customer experience, and other telecom-focused initiatives.
• Work closely with cross-functional teams, including data engineers, data scientists, and business stakeholders.
• Communicate technical concepts and project outcomes effectively to both technical and non-technical audiences.
• Assist with troubleshooting and resolving data-related issues within Palantir Foundry.

Requirements

• Experience with Palantir Foundry.
• Proficiency in SQL and Python.
• Strong background in data engineering and data analysis.
• Familiarity with telecom data structures and standards.
• Knowledge of network planning and operations.

Nice-to-haves

• Experience with machine learning model deployment.
• Understanding of telecom-specific datasets and data standards.