Senior Data Engineer

Univision•Los Angeles, CA

About The Position

TelevisaUnivision is expanding its global streaming platform, ViX, and investing in technology, data, and innovation to improve subscriber experiences and support business growth. The Data Engineering team designs, builds, and operates high-volume, high-velocity data pipelines for playback and engagement events, subscription data, advertising data, and the analytics data warehouse. The team collaborates with Engineering, Product, Data Science, and Analytics teams across the company. The Senior Data Engineer designs, develops, and deploys the streaming data platform and owns production data pipelines end to end, from real-time ingestion through modeled, analytics-ready data. The role partners with data science, analytics, and product teams to understand data needs and deliver initiatives. It calls for strong technical expertise, collaboration, problem-solving, and a focus on high-quality solutions at scale.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
At least 7 years of experience in Data Engineering, Data Warehousing, or Big Data environments.
Advanced proficiency in Python and SQL.
Hands-on experience building and owning production-grade, end-to-end data pipelines.
Strong experience with GCP, including BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Composer; AWS experience will also be considered.
Experience with workflow orchestration and transformation tools such as Airflow and dbt.
Experience building real-time or near-real-time data pipelines.
Strong understanding of data warehousing best practices, including relational and dimensional modeling.
Experience with Infrastructure as Code tools such as Pulumi or Terraform.
Solid understanding of distributed data processing frameworks, including Spark.
Strong analytical, troubleshooting, and problem-solving abilities.
Must be authorized to work in the United States.
Applicants must be currently authorized to work in the United States on a full-time basis.
Employment and education will be verified.

Nice To Haves

Experience supporting machine learning and data science workflows.
Familiarity with data observability, data quality frameworks, and CI/CD practices.
Experience working within subscription-based, media, streaming, or digital product organizations.
Experience with Hadoop.

Responsibilities

Design, develop, and maintain scalable, reliable batch data pipelines using Airflow (Cloud Composer), Python, SQL, and dbt.
Build and maintain real-time ingestion pipelines that move event data from Pub/Sub into Cloud Storage and BigQuery using Dataflow.
Build and optimize dimensional data models and workflows in the analytics data warehouse for reporting, analytics, machine learning, and product initiatives.
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 understand business requirements and translate them into technical solutions.
Contribute to data architecture discussions and long-term platform strategy.
Work with stakeholders to identify 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 pipeline and platform issues, and contribute to incident reviews.
Implement best practices for data governance, observability, testing, and CI/CD.
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.