Senior Data Engineer

Senior Data EngineerAt 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 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.The Senior Data Engineer will play a key role in the design, development, and deployment of our streaming data platform. You will own production data pipelines end to end, from real-time ingestion through modeled, analytics-ready data, and partner with data science, analytics, and product teams to understand their data needs and drive initiatives 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.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), including BigQuery, Pub/Sub, Dataflow, and Cloud ComposerStrong proficiency in Python, SQL, and data transformation frameworks such as dbtHands-on experience building both batch and real-time (streaming) data pipelines at scaleExperience working with large-scale distributed systems and big data technologies, including Spark and HadoopExperience with Infrastructure as Code (IaC) tools such as Pulumi or TerraformExcellent problem-solving skills with the ability to design scalable and efficient solutionsStrong attention to detail and the ability to manage multiple priorities effectivelyOutstanding communication and collaboration skills, with the ability to partner across technical and non-technical teamsA continuous improvement mindset and passion for mentoring and knowledge sharingYour day-to-day (Responsibilities):Data Platform DevelopmentDesign, develop, and maintain scalable, reliable, and efficient batch data pipelines using Airflow (Cloud Composer), Python, SQL, and dbtBuild and maintain real-time ingestion pipelines that land event data from Pub/Sub into Cloud Storage and BigQuery using DataflowBuild and optimize dimensional data models and workflows in the analytics data warehouse to support reporting, analytics, machine learning, and product initiativesOwn assigned pipelines end to end, from design and development through testing, deployment, and production supportEnsure data quality, integrity, security, and availability across the data ecosystemCross-Functional CollaborationPartner with Product Managers, Data Scientists, Analysts, and Engineering teams to understand business requirements and translate them into technical solutionsContribute to data architecture discussions and long-term platform strategyCollaborate with stakeholders to identify opportunities for process improvements and operational efficienciesPerformance & OptimizationOptimize data storage, processing, and orchestration for performance, scalability, and cost efficiency, including BigQuery query and storage costsMonitor, troubleshoot, and resolve data pipeline and platform issues, and contribute to incident reviewsImplement best practices for data governance, observability, testing, and CI/CDLeadership & Team ContributionMentor and support junior data engineers through technical guidance, code reviews, and knowledge sharingContribute to architectural decisions and engineering best practicesParticipate in technical interviews and help grow a high-performing data engineering teamYou have: (Qualifications, Experience)Required Experience & SkillsBachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field7+ years of experience in Data Engineering, Data Warehousing, or Big Data environmentsAdvanced proficiency in Python and SQLHands-on experience building and owning production-grade, end-to-end data pipelinesStrong experience with Google Cloud Platform (GCP), including BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Composer; AWS experience will also be consideredExperience with workflow orchestration and transformation tools such as Airflow and dbtExperience building real-time or near-real-time data pipelinesStrong understanding of data warehousing best practices, including relational and dimensional modelingExperience with Infrastructure as Code (IaC) tools such as Pulumi or TerraformSolid understanding of distributed data processing frameworks, including SparkStrong analytical, troubleshooting, and problem-solving abilitiesPreferred QualificationsExperience supporting machine learning and data science workflowsFamiliarity with data observability, data quality frameworks, and CI/CD practicesExperience working within subscription-based, media, streaming, or digital product organizationsEligibility RequirementsMust be authorized to work in the United StatesEmployment/education will be verifiedApplicants must be currently authorized to work in the United States on a full-time basisOur Benefits:TelevisaUnivision believes that a happy, well-balanced employee is what makes our culture thrive. We offer a wide selection of perks and benefits including PTO, tuition reimbursement, wellness and employee support programs, 401(k), and life and other insurance plans.This is in addition to a comprehensive and competitive health benefits package featuring medical, dental, and vision coverage options.TelevisaUnivision is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to characteristics protected by law.