Senior Data Engineer

TelevisaUnivision • Miami, FL

3d

About The Position

TelevisaUnivision is a Spanish-language media company expanding its global streaming platform, ViX. The Data Engineering team builds and operates high-volume, high-velocity data pipelines for playback and engagement events, subscription and advertising data, and the analytics data warehouse. The Senior Data Engineer will design, develop, deploy, and operate the streaming data platform, owning production pipelines from real-time ingestion through modeled, analytics-ready data. The role partners with engineering, product, data science, and analytics teams to understand data needs and deliver scalable solutions.

The position develops batch and streaming pipelines using Google Cloud Platform services and modern data tools, builds and optimizes warehouse models, and ensures data quality, integrity, security, and availability. It also involves improving performance and cost efficiency, monitoring and troubleshooting production systems, contributing to platform architecture and engineering practices, and mentoring junior engineers.

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 Google Cloud Platform, 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.
• Authorization 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 in subscription-based, media, streaming, or digital product organizations.
• Experience with large-scale distributed systems and big data technologies, including Spark and Hadoop.
• Passion for mentoring and knowledge sharing.

Responsibilities

• Design, develop, and maintain scalable 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 analytics data warehouse workflows for reporting, analytics, machine learning, and product initiatives.
• 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.
• 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.

Benefits

• Paid time off (PTO).
• Tuition reimbursement.
• Wellness and employee support programs.
• 401(k).
• Life and other insurance plans.
• Medical, dental, and vision coverage options.

What This Job Offers

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