Engineer 3, Data Engineer-Xumo

ComcastIrvine, CA
1d

About The Position

Xumo, a joint venture between Comcast and Charter Communications, was formed to develop and offer a next-generation streaming platform for the entire entertainment industry. The company consists of three primary lines of business: Xumo devices, Xumo Play, and Xumo Enterprise. Powered by Comcast’s global entertainment platform, Xumo devices feature a world-class user interface with universal voice search capabilities, making it easy for consumers to find and enjoy their favorite streaming content. Xumo Play is a free ad-supported streaming TV (FAST) service offering hundreds of linear channels and on-demand options. Xumo Enterprise provides tools and services for content creators, distributors, and advertisers to make FAST content more accessible. Job Summary The Data Engineer will play a pivotal role in extracting, transforming, and analyzing data to provide actionable insights and drive data-informed decisions. This role involves designing and implementing data pipelines, building data models, and developing analytical solutions to optimize ad performance and operational efficiency. The ideal candidate will have a strong background in data engineering, analytics, and a solid understanding of digital advertising principles.

Requirements

  • Strong programming skills in Python, SQL.
  • Experience with data pipeline development and ETL/ELT processes.
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Proficiency in working with both relational and NoSQL databases.
  • Experience with cloud-based data platforms (e.g., AWS, Google Cloud).
  • Clear understanding of Data Warehousing concepts and technologies.
  • Experience with data visualization tools (e.g., Tableau, Power BI, Looker, Periscope/Sisense).
  • Strong analytical and problem-solving skills.
  • Understanding of digital advertising principles and metrics.
  • Understanding of data governance.

Nice To Haves

  • Knowledge of machine learning techniques and applications.
  • Knowledge of Data Modeling.
  • Experience with real-time data processing and streaming.
  • Familiarity with ad server technologies and protocols (e.g., VAST, VPAID).
  • Experience with version control systems (Git).
  • Experience with data quality tools.

Responsibilities

  • Data Pipeline Development: Design, develop, and maintain robust data pipelines to ingest data from various sources into Xumo’s Enterprise Data Warehouse. Also process and store data from various sources (e.g., ad serving logs, campaign data, user behavior data). Monitor data pipeline performance and identify areas for optimization.
  • Data Modeling and Warehousing: Develop and maintain data models and schemas optimized for analytical querying and reporting. Design and implement data warehousing solutions to support efficient data storage and retrieval. Work with cloud-based data platforms (e.g., Google BigQuery, Snowflake). Clear understanding of Enterprise Data Warehouse concepts.
  • Analytical Solutions Development: Develop and implement analytical solutions, including dashboards, reports, and visualizations, to monitor ad performance, identify trends, and provide actionable insights. Utilize data mining and statistical techniques to uncover data patterns and correlations in ad data. Build and maintain reporting systems that provide key performance indicators (KPIs) related to ad campaigns and system performance. Analyze ad performance data to identify opportunities for campaign optimization and revenue growth. Provide data-driven recommendations to improve ad targeting, delivery, and reporting.
  • Performance Monitoring and Optimization: Implement ETL/ELT processes to transform raw data into a structured, normalized enterprise level Data Marts in a usable format for analysis. Ensure data quality, consistency, and reliability throughout the various lifecycle of the ingested data.
  • Collaboration and Communication: Collaborate with software engineers, product managers, and other stakeholders to understand data requirements and deliver data-driven solutions. Communicate complex data insights effectively to both technical and non-technical audiences. Work closely with the QA team to validate data accuracy.
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