{"id":2909440,"url":"https://alion.io/job/televisaunivision-principal-data-engineer","title":"Principal Data Engineer","company":{"id":1774589,"name":"TelevisaUnivision","domain":"televisaunivision.com","url":"https://alion.io/company/televisaunivision","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":7,"ghost_share":0,"stale_share":0.714,"repost_share":0,"time_to_fill_p50_days":36,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Miami, United States","Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":102000,"max_usd":200000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":415},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Incident Management","optional":false},{"name":"LLM","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-19T00:00:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T02:43:43Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"ABOUT THE ROLE & TEAM:\nAt 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.\nThe 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.\nThe Principal Data Engineer will play a key role as a technical leader in the design, development, and deployment of our data platform. You will be critical in setting the architecture and multi-year technical direction for our data platform, stay hands-on with the hardest real-time and batch data problems, and mentor junior and mid-level engineers to raise the engineering bar across the team.\nThe ideal candidate pairs deep hands-on expertise in streaming and distributed data systems with the judgment to make long-lived platform decisions, the influence to align teams without direct authority, and a genuine commitment to growing other engineers.\nAbout You\nYou are a hands-on technical leader who designs platforms, not just pipelines. You are equally comfortable writing production code, defending an architecture in a design review, pairing with a junior engineer on a tricky problem, and explaining trade-offs to executives.\nYou bring:\nExpert-level knowledge of Google Cloud Platform data services, especially BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer, and Cloud Storage\nDeep experience designing real-time and event-driven architectures with exactly-once semantics, late-arriving data, and schema evolution\nMastery of Python and SQL, and data transformation frameworks such as dbt\nA track record of setting technical direction for a platform used by many teams, and seeing it through multi-quarter delivery\n· Experience with Infrastructure as Code (IaC) tools such as Pulumi or Terraform\n· Excellent problem-solving skills with the ability to design scalable and efficient solutions\n· Strong attention to detail and the ability to manage multiple priorities effectively\n· Outstanding communication and collaboration skills, with the ability to partner across technical and non-technical teams\n· A continuous improvement mindset and passion for mentoring and knowledge sharing\nA passion for mentoring junior engineers and building a strong engineering culture\nYour Day-to-Day (Responsibilities)\nData Platform Architecture, Development & Technical Strategy\n· Build reference implementations, frameworks, and reusable libraries that other engineers adopt, covering ingestion templates, dbt and Airflow patterns, and IaC modules in Pulumi\nLead the design of real-time pipelines on Pub/Sub and Dataflow, including event schemas, schema registry and evolution, exactly-once processing, watermarking, and late-data handling\n· Own assigned pipelines end to end, from design and development through testing, deployment, and production support\n· Ensure data quality, integrity, security, and availability across the data ecosystem\nCross-Functional Collaboration\n· Partner with Product Managers, Data Scientists, Analysts, and Engineering teams to understand business requirements and translate them into technical solutions\n· Contribute to data architecture discussions and long-term platform strategy\n· Collaborate with stakeholders to identify opportunities for process improvements and operational efficiencies\nPerformance & Optimization\n· Optimize data storage, processing, and orchestration for performance, scalability, and cost efficiency, including BigQuery query and storage costs\n· Monitor, troubleshoot, and resolve data pipeline and platform issues, and contribute to incident reviews\n· Implement best practices for data governance, observability, testing, and CI/CD\nLead incident response for severe data incidents, run blameless postmortems, and drive systemic fixes\nLeadership & Team Contribution\n· Mentor and support junior data engineers through technical guidance, code reviews, and knowledge sharing\n· Contribute to architectural decisions and engineering best practices\n· Participate in technical interviews and help grow a high-performing data engineering team\nEvaluate and drive adoption of emerging technologies, including AI-assisted engineering workflows and LLM-enabled data tooling, while maintaining strong quality and security standards\nYou Have (Qualifications & Experience)\nRequired Experience & Skills\nBachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent experience\n12+ years of experience in Data Engineering, Data Warehousing, or Big Data environments\n2+ years in a Tech-lead role setting technical direction across teams\nDemonstrated experience mentoring and developing junior and mid-level engineers\nProven track record designing and running real-time data platforms in production at high volume, for example billions of events per day\nExpert-level experience with GCP: BigQuery, Pub/Sub, Dataflow (Apache Beam), Cloud Composer (Airflow), and Cloud Storage; AWS experience will also be considered\nExpert-level Python and SQL, and production experience with dbt\nDeep knowledge of stream processing concepts: event time vs. processing time, windowing, watermarks, exactly-once delivery, and backpressure; Kafka, Flink, or Spark\nExpert understanding of data modeling for analytics, including dimensional modeling, event modeling, and lakehouse table formats such as Apache Iceberg\nStrong experience with Infrastructure as Code (Pulumi or Terraform), CI/CD, and automated testing for data pipelines\nDemonstrated ownership of data reliability: SLOs, data observability, incident management, and postmortems\nDemonstrated success reducing cloud data platform cost at scale\nExcellent written, verbal, and presentation skills, including design documents and communication with technical and executive audiences\nPreferred Qualifications\nExperience in subscription, streaming video (OTT), media, or sports organizations, including playback quality, engagement, and ad-supported (AVOD) data\nExperience supporting ML and data science workloads: feature pipelines, real-time features, recommendation and personalization data\nExperience with data contracts, schema registries, and data catalog or lineage tools\nELIGIBILITY REQUIREMENTS\nMust be authorized to work in the United States\nEmployment/education will be verified\n· Applicants must be currently authorized to work in the United States on a full-time basis\n\nOur Benefits\nTelevisaUnivision 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.\nThis is in addition to a comprehensive and competitive health benefits package featuring medical, dental, and vision coverage options.\nTelevisaUnivision is an equal opportunity employer. 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