Principal Data Engineer

TelevisaUnivision • Miami, FL

3d

About The Position

TelevisaUnivision is expanding its global streaming platform, ViX, and investing in technology, data, and innovation. The Data Engineering team designs, builds, and operates high-volume, high-velocity pipelines for playback and engagement events, subscription data, advertising data, and the analytics data warehouse. It collaborates with Engineering, Product, Data Science, and Analytics teams across the company.

The Principal Data Engineer is a hands-on technical leader responsible for shaping the architecture and multi-year technical direction of the data platform while tackling complex real-time and batch data problems. The role sets technical direction across teams, builds reusable platform components, owns pipelines through production support, and mentors engineers. It also involves aligning stakeholders, making long-lived platform decisions, and improving the reliability, scalability, performance, and cost efficiency of data systems.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience.
• 12+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
• 2+ years in a Tech-lead role setting technical direction across teams.
• Demonstrated experience mentoring and developing junior and mid-level engineers.
• Proven track record designing and operating high-volume production real-time data platforms, such as those processing billions of events per day.
• Expert-level experience with GCP services including BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer (Airflow), and Cloud Storage; AWS experience will also be considered.
• Expert-level Python and SQL skills and production experience with dbt.
• Deep knowledge of stream processing concepts, including event time versus processing time, windowing, watermarks, exactly-once delivery, and backpressure; experience with Kafka, Flink, or Spark.
• Expert understanding of analytics data modeling, including dimensional modeling, event modeling, and lakehouse table formats such as Apache Iceberg.
• Strong experience with Infrastructure as Code (Pulumi or Terraform), CI/CD, and automated testing for data pipelines.
• Demonstrated ownership of data reliability, including SLOs, data observability, incident management, and postmortems.
• Demonstrated success reducing cloud data platform costs at scale.
• Excellent written, verbal, and presentation skills, including design documents and communication with technical and executive audiences.
• Must be authorized to work in the United States on a full-time basis; employment and education will be verified.

Nice To Haves

• Experience in subscription, streaming video (OTT), media, or sports organizations, including playback quality, engagement, and ad-supported (AVOD) data.
• Experience supporting machine learning and data science workloads, including feature pipelines, real-time features, recommendation, and personalization data.
• Experience with data contracts, schema registries, and data catalog or lineage tools.

Responsibilities

• Build reference implementations, frameworks, and reusable libraries for ingestion templates, dbt and Airflow patterns, and Pulumi infrastructure modules.
• Lead the design of real-time pipelines on Pub/Sub and Dataflow, including event schemas, schema registry and evolution, exactly-once processing, watermarking, and late-data handling.
• Own assigned pipelines from design and development through testing, deployment, and production support.
• Ensure data quality, integrity, security, and availability across the data ecosystem.
• Partner with Product Managers, Data Scientists, Analysts, and Engineering teams to translate business requirements into technical solutions.
• Contribute to data architecture discussions and long-term platform strategy.
• Identify opportunities for process improvements and operational efficiencies with stakeholders.
• Optimize data storage, processing, and orchestration for performance, scalability, and cost efficiency, including BigQuery query and storage costs.
• Monitor, troubleshoot, and resolve data pipeline and platform issues, and contribute to incident reviews.
• Implement best practices for data governance, observability, testing, and CI/CD.
• Lead response to severe data incidents, run blameless postmortems, and drive systemic fixes.
• Mentor junior data engineers through technical guidance, code reviews, and knowledge sharing.
• Contribute to architectural decisions and engineering best practices.
• Participate in technical interviews and help grow the data engineering team.
• Evaluate and drive adoption of emerging technologies, including AI-assisted engineering workflows and LLM-enabled data tooling, while maintaining quality and security standards.

Benefits

• PTO
• Tuition reimbursement
• Wellness and employee support programs
• 401(k)
• Life and other insurance plans
• Comprehensive health benefits, including medical, dental, and vision coverage options

What This Job Offers

• Job Type: Full-time
• Career Level: Principal