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About the Role

TelevisaUnivision is the world's leading Spanish-language media company, expanding its global streaming platform, ViX. The Data Engineering team builds and operates high-volume, high-velocity data pipelines for ViX, supporting various data types and analytics. The Principal Data Engineer will be a technical leader, responsible for the architecture and technical direction of the data platform, while remaining hands-on with complex data challenges and mentoring other engineers.

Responsibilities

Build reference implementations, frameworks, and reusable libraries for other engineers, including ingestion templates, dbt and Airflow patterns, and IaC modules in Pulumi.
Lead the design of real-time pipelines on Pub/Sub and Dataflow, covering event schemas, schema registry and evolution, exactly-once processing, watermarking, and late-data handling.
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 data ecosystem.
Partner 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 long-term platform strategy.
Collaborate with stakeholders to identify opportunities for process improvements and operational efficiencies.
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 incident response for severe data incidents, run blameless postmortems, and drive systemic fixes.
Mentor and support 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 a high-performing data engineering team.
Evaluate and drive adoption of emerging technologies, including AI-assisted engineering workflows and LLM-enabled data tooling, while maintaining strong quality and security standards.

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 running real-time data platforms in production at high volume, for example billions of events per day.
Expert-level experience with GCP: BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer (Airflow), and Cloud Storage; AWS experience will also be considered.
Expert-level Python and SQL, and production experience with dbt.
Deep knowledge of stream processing concepts: event time vs. processing time, windowing, watermarks, exactly-once delivery, and backpressure; Kafka, Flink, or Spark.
Expert understanding of data modeling for analytics, 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: SLOs, data observability, incident management, and postmortems.
Demonstrated success reducing cloud data platform cost at scale.
Excellent written, verbal, and presentation skills, including design documents and communication with technical and executive audiences.
Experience in subscription, streaming video (OTT), media, or sports organizations, including playback quality, engagement, and ad-supported (AVOD) data.
Experience supporting ML and data science workloads: feature pipelines, real-time features, recommendation and personalization data.
Experience with data contracts, schema registries, and data catalog or lineage tools.
Must be authorized to work in the United States.
Employment/education will be verified.
Applicants must be currently authorized to work in the United States on a full-time basis.

Skills

Google Cloud Platform (GCP) data services
BigQuery
Pub/Sub
Dataflow (Apache Beam)
Cloud Composer
Cloud Storage
Real-time architectures
Event-driven architectures
Exactly-once semantics
Late-arriving data
Schema evolution
Python
SQL
dbt
Infrastructure as Code (IaC)
Pulumi
Terraform
Problem-solving
Scalable solutions
Efficient solutions
Attention to detail
Managing multiple priorities
Communication
Collaboration
Continuous improvement
Mentoring
Knowledge sharing
Data Platform Architecture
Data Platform Development
Technical Strategy
Data ingestion
Airflow patterns
Event schemas
Schema registry
Watermarking
Late-data handling
Data quality
Data integrity
Data security
Data availability
Data ecosystem
Product Management
Data Science
Analytics
Business requirements
Technical solutions
Data architecture
Platform strategy
Process improvements
Operational efficiencies
Data storage optimization
Data processing optimization
Orchestration optimization
Performance optimization
Scalability optimization
Cost efficiency
BigQuery query costs
BigQuery storage costs
Monitoring
Troubleshooting
Data pipeline issues
Platform issues
Incident reviews
Data governance
Observability
Testing
CI/CD
Incident response
Blameless postmortems
Systemic fixes
Leadership
Team Contribution
Technical guidance
Code reviews
Architectural decisions
Engineering best practices
Technical interviews
Emerging technologies
AI-assisted engineering workflows
LLM-enabled data tooling
Quality standards
Security standards
Data Warehousing
Big Data environments
Tech-lead
Stream processing concepts
Event time
Processing time
Windowing
Watermarks
Exactly-once delivery
Backpressure
Kafka
Flink
Spark
Data modeling for analytics
Dimensional modeling
Event modeling
Lakehouse table formats
Apache Iceberg
Automated testing
Data reliability
SLOs
Data observability
Incident management
Postmortems
Cloud data platform cost reduction
Written communication
Verbal communication
Presentation skills
Design documents
Executive communication
Subscription data
Streaming video (OTT) data
Media data
Sports data
Playback quality data
Engagement data
Ad-supported (AVOD) data
ML workloads
Data science workloads
Feature pipelines
Real-time features
Recommendation data
Personalization data
Data contracts
Data catalog tools
Data lineage tools

Location

United States

Work Type

Full-time

Experience Level

Principal
12+ years of experience
2+ years in a Tech-lead role
Demonstrated experience mentoring and developing junior and mid-level engineers

Education Level

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience.

Benefits

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

About the Company

TelevisaUnivision is the world's leading Spanish-language media company, reaching millions of consumers across digital, streaming, social, audio, linear television, and live events.
We are investing heavily in technology, data, and innovation to deliver exceptional subscriber experiences and drive long-term business growth.
The Data Engineering team designs, builds, and operates the high-volume, high-velocity data pipelines that power ViX, including playback and engagement events, subscription data, advertising data, and the analytics data warehouse that turns them into business decisions.
The team works closely with Engineering, Product, Data Science, and Analytics teams across TelevisaUnivision.

Equal Opportunity

TelevisaUnivision is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to characteristics protected by law.