Senior Data Engineer, National Traffic and Capacity Management

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Job Summary

Join our National Traffic and Capacity Management (NTCM) team at Comcast as a Data Analysis Engineer IV and play a crucial role in optimizing network capacity management. You will support new product line capacity management needs: EOHFC, EPON vBNG, Xfinity Mobile etc. Support the ML models for LRP and Budget planning for FDX. You'll build and maintain robust data pipelines, enabling critical analysis and data science initiatives that drive our network's performance. The ideal candidate will be a proactive problem-solver, adept at identifying and resolving gaps, automating processes, and ensuring data readiness for diverse applications. You'll also have the opportunity to delve into ad-hoc data analysis and explore machine learning and predictive modeling, contributing to strategic decision-making.

Job Description

We are seeking a highly skilled and collaborative Senior Data Engineer to design, build, and maintain robust data infrastructure and pipelines that power analytics, reporting, and machine learning across the organization. This role requires a strong foundation in data engineering, cloud platforms, and data governance, as well as the ability to translate complex business requirements into scalable technical solutions. The ideal candidate also has experience mentoring team members and is prepared to lead junior engineers.

Core Responsibilities

• Design, develop, and maintain scalable data pipelines, BI applications, and information systems (e.g., data lakes, warehouses) to support advanced analytics and reporting.
• Engineer and optimize data ingestion, transformation, and mining processes for structured and unstructured data, ensuring high performance and scalability.
• Ensure data quality across the lifecycle—from ingestion to final load—by implementing robust validation, monitoring, and quality assurance practices.
• Develop and maintain reusable frameworks and APIs for data access and consumption by downstream applications and end users.
• Technical product management: partner with stakeholders to gather, analyze, and translate business and technical requirements into scalable data solutions, ensuring alignment with product goals and user needs.
• Collaborate cross-functionally with peers, platform teams, and stakeholders to align on data architecture, sourcing strategies, and process improvements.
• Support machine learning initiatives and perform ad hoc data analysis to drive business insights and innovation.
• Administer cloud and on-prem data platforms, including Kubernetes, Teradata, AWS (S3, Redshift), and Databricks, selecting appropriate storage based on sensitivity and access needs.
• Document system designs, processes, and data lineage to support transparency, troubleshooting, and impact analysis.
• Apply data governance and privacy standards, ensuring compliance with customer data protection and lifecycle management policies.

Required Qualifications

• Bachelor’s degree in Engineering, Computer Science, Mathematics, Finance, or a related field (or equivalent experience).
• Minimum of 8 years of experience in data engineering, analytics, or a related technical field.
• Demonstrated ability to leverage AI/ML tools and models in engineering workflows to enhance productivity, problem-solving, and innovation—including emerging agentic AI systems that can plan, reason, and act autonomously.
• Expert proficiency in SQL and Python, with hands-on experience in data engineering, ETL processes, pipeline automation, and data quality assurance.
• Strong experience with AWS and Databricks for data processing and storage.
• Proficiency with business intelligence tool