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TelevisaUnivision

Global Spanish-language media company and distributor

Principal Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeMexico City, CDMX, MexicoNo salary listed

About the Job

Requirements

  • Bachelor's or master's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience.
  • More than 12 years of experience in Data Engineering, Data Warehousing, or Big Data environments.
  • At least 2 years of experience in a technical leadership role defining technical direction across multiple teams.
  • Demonstrated experience mentoring and developing junior- and mid-level engineers.
  • Proven experience designing and operating high-volume, real-time production data platforms, such as platforms processing billions of events per day.
  • Expert experience with Google Cloud Platform (GCP), including BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer (Airflow), and Cloud Storage; AWS experience is also considered.
  • Expert proficiency in Python and SQL, and production experience with dbt.
  • Deep knowledge of streaming data processing concepts, including event time versus processing time, windowing, watermarks, exactly-once delivery, and backpressure; experience with Kafka, Flink, or Spark.
  • Expert knowledge of data modeling for analytics, including dimensional modeling, event modeling, and lakehouse table formats such as Apache Iceberg.
  • Extensive experience with Infrastructure as Code (Pulumi or Terraform), continuous integration and delivery (CI/CD), and automated testing for data pipelines.
  • Demonstrated experience managing data reliability, including service-level objectives (SLOs), data observability, incident management, and post-incident reviews.
  • Proven experience reducing costs for large-scale cloud data platforms.
  • Excellent written, verbal, and presentation skills, including producing design documents and communicating with technical and executive audiences.
  • Availability to work in Mexico City.
  • Employment and academic history will be verified.

Responsibilities

  • Develop reference implementations, frameworks, and reusable libraries for other engineers, including data-ingestion templates, dbt and Airflow patterns, and Pulumi Infrastructure as Code modules.
  • Lead the design of real-time data pipelines using Pub/Sub and Dataflow, including event schemas, registries and schema evolution, exactly-once processing, watermarking, and handling late-arriving data.
  • Own assigned pipelines end to end, from design and development through testing, deployment, and production support.
  • Ensure data quality, integrity, security, and availability across the ecosystem.
  • Collaborate with Product Managers, Data Scientists, Analysts, and Engineering teams to understand business requirements and translate them into technical solutions.
  • Contribute to data architecture discussions and the platform's long-term strategy.
  • Work with stakeholders to identify process-improvement and operational-efficiency opportunities.
  • Optimize data storage, processing, and orchestration to improve performance, scalability, and cost efficiency, including BigQuery query and storage costs.
  • Monitor, diagnose, and resolve data-pipeline and platform issues, and contribute to incident reviews.
  • Implement best practices for data governance, observability, testing, and continuous integration and delivery (CI/CD).
  • Lead responses to major data incidents, conduct blameless postmortems, and drive structural solutions to prevent recurrence.
  • Mentor and support junior data engineers through technical guidance, code reviews, and knowledge sharing.
  • Contribute to architectural decisions and the definition of engineering best practices.
  • Participate in technical interviews and support the development of a high-performing Data Engineering team.
  • Evaluate and promote emerging technologies, including AI-assisted engineering workflows and large language model (LLM)-based data tools, while maintaining high quality and security standards.

Desired Qualifications

  • Experience in subscription businesses, over-the-top (OTT) streaming video platforms, media, or sports organizations, including playback-quality, user-engagement, and advertising data on ad-supported video on demand (AVOD) platforms.
  • Experience supporting Machine Learning and Data Science workloads, including feature pipelines, real-time features, and data for recommendation and personalization systems.
  • Experience with data contracts, schema registries, and data cataloging or lineage tools.

About the Company

TelevisaUnivision

Global Spanish-language media company and distributor

TelevisaUnivision is a media company that operates Spanish-language television networks, streaming services, and content production and distribution for audiences in the United States and Latin America. It creates and acquires Spanish-language programming and distributes it through TV networks, cable/satellite providers, and direct-to-consumer platforms, using a unified catalog across borders. The company differentiates itself as the world’s largest Spanish-language media business, leveraging Televisa’s Mexican assets and Univision’s U.S. networks and distribution to reach a broad audience and attract advertisers. Its goal is to be the leading global platform for Spanish-language entertainment and information, serving diverse, culturally relevant content wherever viewers watch.

Company size
5,001-10,000
Company stage
Debt Financing
Total funding
$4.3B
Headquarters
Doral, FL
Founded
1962

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