Senior Data Engineer

Requirements

• 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
• ELIGIBILITY REQUIREMENTS
• Must be authorized to work in the United States
• Must be willing to work from our Miami, Florida office
• Employment and educational background verification required

Benefits

Additional Information

At TelevisaUnivision, we are the world's leading Spanish-language media company, reaching millions of consumers across digital, streaming, social, audio, linear television, and live events. As we continue expanding our global streaming platform, ViX, we are investing heavily in technology, data, and innovation to deliver exceptional subscriber experiences and drive long-term business growth. The Senior Data Engineer will play a key role in the design, development, and deployment of our data platform. The ideal candidate will have a strong technical background in data engineering and be experienced in building and maintaining large-scale data systems. The Senior Data Engineering will work closely with other teams, such as data science and product development, to understand their data needs and ensure initiatives are driven to completion. The ideal candidate combines strong technical expertise with a collaborative mindset, a passion for solving complex data challenges, and a commitment to delivering high-quality solutions at scale. ABOUT YOU: You are a data engineering professional who thrives in a fast-paced, collaborative environment and enjoys transforming complex data into actionable business value. You bring: Deep expertise in modern cloud-based data platforms, particularly Google Cloud Platform (GCP) Strong proficiency in Python, SQL, and data transformation frameworks such as dbt Experience working with large-scale distributed systems and big data technologies, including Spark, and Hadoop Experience with Infrastructure as Code (IaC) tools such as Pulumi or Terraform 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, with the ability to partner across technical and non-technical teams A continuous improvement mindset and passion for mentoring and knowledge sharing YOUR DAY-DAY: (Responsibilities) Data Platform Development Design, develop, and maintain scalable, reliable, and efficient data pipelines using Airflow, Python, SQL, and dbt to support business requirements Build and optimize data models and workflows to support analytics, reporting, machine learning, and product initiatives Ensure data quality, integrity, security, and availability across the data ecosystem Cross-Functional Collaboration Partner with Product Managers, Data Scientists, Analysts, and Engineering teams to understand business requirements and translate them into technical solutions Drive data architecture discussions and contribute to long-term platform strategy Collaborate with stakeholders to identify opportunities for process improvements and operational efficiencies Performance & Optimization Optimize data storage, processing, and orchestration for performance, scalability, and cost efficiency Monitor, troubleshoot, and resolve data pipeline and platform issues Implement best practices for data governance, observability, and operational excellence Leadership & Team Contribution Mentor and support junior data engineers through technical guidance and knowledge sharing Contribute to architectural decisions and engineering best practices Participate in technical interviews and help grow a high-performing data engineering team YOU HAVE: (Qualifications, Experience) Required Experience & Skills Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field 5+ years of experience in Data Engineering, Data Warehousing, or Big Data environments Advanced proficiency in Python and SQL Hands-on experience building and maintaining production-grade data pipelines Strong experience with cloud data platforms, preferably Google Cloud Platform (GCP); AWS experience will also be considered Experience with workflow orchestration and transformation tools such as Airflow and dbt Experience with Infrastructure as Code (IaC) tools such as Pulumi or Terraform Solid understanding of distributed data processing frameworks, including Spark Experience working with modern data warehousing and storage technologies Strong analytical, troubleshooting, and problem-solving abilities

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