Job Summary
Responsible for designing, building and overseeing the deployment and operation of technology architecture, solutions and software to capture, manage, store and utilize structured and unstructured data from internal and external sources. Establishes and builds processes and structures based on business and technical requirements to channel data from multiple inputs, route appropriately and store using any combination of distributed (cloud) structures, local databases, and other applicable storage forms as required. Develops technical tools and programming that leverage artificial intelligence, machine learning and big-data techniques to cleanse, organize and transform data and to maintain, defend and update data structures and integrity on an automated basis. Creates and establishes design standards and assurance processes for software, systems and applications development to ensure compatibility and operability of data connections, flows and storage requirements. Reviews internal and external business and product requirements for data operations and activity and suggests changes and upgrades to systems and storage to accommodate ongoing needs. Work with data modelers/analysts to understand the business problems they are trying to solve then create or augment data assets to feed their analysis. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience.Job Description
Must-Have Skills & Experience (Core Capabilities):
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Strong understanding of distributed data processing systems and Spark architecture
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Hands-on experience building and owning end-to-end data pipelines (design, development, deployment, monitoring, and optimization)
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Solid data modeling skills for analytical and reporting use cases
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Proven ability to debug, troubleshoot, and resolve production data pipeline issues
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Experience with performance tuning and optimization of large-scale data workloads
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Strong focus on data quality, validation, and reliability
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Experience working with modern data lake / lakehouse architectures (e.g., Delta Lake or similar)
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Ability to make informed decisions around cluster sizing, resource utilization, and cost–performance trade-offs
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Strong problem-solving skills and an ownership mindset for production systems Nice-to-Have Skills (Accelerators)
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Experience with advanced Python data libraries such as Pandas, NumPy, Polars, or DuckDB
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Exposure to AI/ML workflows, feature engineering, or data preparation for models
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Experience working in cloud environments (AWS, Azure, or GCP)
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Familiarity with CI/CD practices for data pipelines
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Exposure to DevOps or platform engineering concepts
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Experience with serverless or event-driven components (e.g., AWS Lambda
We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools that are personalized to meet the needs of your reality—to help support you physically, financially and emotionally through the big milestones and in your everyday life.
Please visit the benefits summary on our careers site for more details.
Education
Bachelor's DegreeWhile possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.Certifications (if applicable)
Relevant Work Experience
5-7 YearsComcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.
