Staff Data Engineer (Python, AI/ML) – REMOTE

Staff Data Engineer (Python, AI/ML) – RemoteLocation: Remote (U.S. Only)Compensation: $220,000 – $240,000 per year + full benefitsAbout the Opportunity An international media and digital analytics organization is seeking a Staff Data Engineer to help lead the evolution of its data platforms and AI capabilities. This is a senior, high-impact technical role focused on large-scale data architecture, cross-platform integration, and AI/LLM-driven product development. You'll work across multiple teams to shape long-term architecture, drive innovation, and ensure systems scale effectively as the organization grows.Key ResponsibilitiesDesign and own scalable, cross-platform data architecture across complex systemsLead integration of data platforms to enable unified insights and product capabilitiesBuild and optimize data pipelines (batch + streaming) and data models at scale using Python and modern data frameworksDevelop and maintain production-grade Python code for data processing, automation, and AI/ML workflowsDrive development and deployment of AI/ML and LLM-powered featuresEstablish best practices for data modeling, pipeline design, and system observabilityMentor engineers and raise the technical bar across teamsTranslate business needs into clear, scalable architectural decisionsContribute to architecture reviews, roadmap planning, and on-call support for production systemsRequired Qualifications (Must-Have)8+ years of experience in data engineering or data architectureProven experience working in complex, multi-system or multi-team environmentsStrong Python expertise (hands-on, production-level development)Experience building AI/ML or LLM-based solutions in productionDeep experience with large-scale data architecture (pipelines, modeling, warehousing)Strong communication skills — able to translate complex technical concepts clearlyDemonstrated success mentoring engineers and elevating team performanceStrongly PreferredExperience with Snowflake, BigQuery, or similar cloud data warehouse platformsFamiliarity with Kafka, Kubernetes, or real-time streaming infrastructureExperience with cross-division or cross-company data/platform integration initiativesPassion for mentorship, teaching, and contributing to engineering culture—not just individual deliveryTechnical EnvironmentCloud data warehouses (Snowflake, BigQuery, or similar)Data processing & orchestration (Spark, Kafka, Airflow, or equivalent)Batch and streaming data pipelinesCloud-native / containerized environments (Kubernetes a plus)What Success Looks LikeFirst 90 days: Deliver an architectural assessment and identify integration opportunities6 months: Advance or deliver a cross-platform data or AI initiative12 months: Own the data architecture roadmap and mentor multiple engineersBenefitsMedical, Dental, and Vision coverage401(k) with company matchGenerous paid parental leaveFlexible work schedule + unlimited PTOMonthly stipends (home office, internet, wellness)Annual company eventCollaborative culture with a strong work-life balance#J-18808-Ljbffr