{"id":1954312,"url":"https://alion.io/job/youtube-data-engineer-youtube-marketing-2","title":"Data Engineer, YouTube Marketing","company":{"id":12362,"name":"YouTube","domain":"youtube.com","url":"https://alion.io/company/youtube","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":85000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":935},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Hadoop","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"Machine Learning","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-10-06T11:11:22Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-24T20:05:35Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"About the job\nAs a Data Engineer for the Global YouTube Marketing team, you will play a vital role in building and maintaining the data infrastructure that fuels our marketing strategy. You will design, develop, and optimize scalable data pipelines, ensuring high data quality and accessibility for analytics and reporting. Your technical expertise will enable the broader marketing organization to leverage data-driven insights to measure and optimize the impact of marketing initiatives.Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.Responsibilities\nDesign, develop, and maintain scalable data pipelines and data models to collect, process, and store data from various marketing sources.\nIntegrate new metrics into core data marts and establish robust data quality checks and monitoring to ensure data accuracy, integrity, and pipeline stability.\nCollaborate with cross-functional partners to translate business requirements into technical data solutions and infrastructure.\nOptimize data infrastructure and querying layers for performance, efficiency, and scalability to support evolving Global YouTube Marketing needs.\nQualifications\nMinimum qualifications:\nBachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.\n3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).\nExperience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.\nExperience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.\nExperience integrating generative AI tools or LLM interfaces into workflows.\nPreferred qualifications:\nExperience in technical consulting.\nExperience working with Big Data, information retrieval, data mining, or machine learning.\nExperience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).\nExperience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.\nExpertise in designing data models, data warehouses, and handling large-scale distributed data 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