As a Principal Data Engineer at Univision communications inc, you will help lead the design, development, and deployment of the data platform that powers ViX. The work spans real-time and batch pipelines, plus an analytics data warehouse, with an emphasis on both technical strategy and hands-on execution across streaming and distributed systems.
What you will do
- Build reference implementations, frameworks, and reusable libraries that other engineers adopt, including ingestion templates, dbt and Airflow patterns, and IaC modules in Pulumi
- Lead real-time pipeline design on Pub/Sub and Dataflow (Apache Beam), 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
- Maintain 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
- Support data architecture discussions and contribute to long-term platform strategy
- Collaborate with stakeholders to identify process improvements and operational efficiencies
- Optimize storage, processing, and orchestration for performance, scalability, and cost efficiency, including BigQuery query and storage costs
- Monitor, troubleshoot, and resolve 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 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
Qualifications
- 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 knowledge of Google Cloud Platform data services, especially BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer, and Cloud Storage
- Deep experience designing real-time and event-driven architectures with exactly-once semantics, late-arriving data, and schema evolution
- Mastery of Python and SQL, and data transformation frameworks such as dbt
- Deep knowledge of stream processing concepts including event time vs. 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: 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 for technical and executive audiences
- Excellent problem-solving skills with the ability to design scalable and efficient solutions
- Strong attention to detail and the ability to manage multiple priorities effectively
- Outstanding communication and collaboration skills across technical and non-technical teams
- Continuous improvement mindset and passion for mentoring and knowledge sharing
- 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
Technologies you will work with
- BigQuery
- Pub/Sub
- Dataflow (Apache Beam)
- Cloud Composer
- Cloud Storage
- Python
- SQL
- dbt
- Apache Airflow
- Pulumi
- Terraform
- Kafka
- Flink
- Spark
- Apache Iceberg
- Infrastructure as Code (IaC)
- CI/CD
- LLM-enabled data tooling
- AI-assisted engineering workflows
Benefits
- PTO
- Tuition reimbursement
- Wellness and employee support programs
- 401(k)
- Life and other insurance plans
- Medical coverage
- Dental coverage
- Vision coverage options
About the team
The Data Engineering team designs, builds, and operates high-volume, high-velocity data pipelines that power ViX, including playback and engagement events, subscription data, advertising data, and the analytics data warehouse used to support business decisions. The team works closely with Engineering, Product, Data Science, and Analytics teams across TelevisaUnivision.
Preferred qualifications
- 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
Location: Miami, FL (onsite)
Minimum experience: 12 years
Eligibility: Must be authorized to work in the United States; employment/education will be verified; full-time authorization required.
