Senior Data Architect - Only USC & local to MN
Job Description:OverviewThe Data & AI Team is building the future of local media by deploying end-to-end, high-impact solutions that solve complex data and AI challenges.This is a net-new role created from splitting a hybrid AI/Data position, now focused on data platform engineering and architecture.The team is seeking a Senior Data Engineer (Platform & Architecture) to lead development, infrastructure, and architectural design of a modern data ecosystem powering analytics, AI, and personalization.Key Focus AreasBuild scalable, production-grade data infrastructure supporting:Analytics & reportingAI initiativesPersonalization & customer intelligenceLead development of Python-based ELT/ETL pipelinesOwn Snowflake platform architecture, performance, and cost optimizationDesign scalable data models and schemas for cross-channel insightsEnable AI-ready data foundations and reusable data productsResponsibilities:Build, deploy, and maintain scalable ELT/ETL pipelines using Python & SQLDevelop reusable data ingestion frameworks and connectorsImplement data quality checks, testing, and anomaly detectionApply agentic development practices (AI-assisted dev, automated testing, documentation)Manage and optimize Snowflake (performance, storage, compute efficiency)Configure compute resources, clustering keys, and scaling policiesAutomate deployments via CI/CD and infrastructure-as-codeDesign high-performance logical and physical data modelsEstablish data governance, lineage, and cataloging standardsEnvironment:Data Platform: SnowflakeEngineering: Python, SQLOrchestration/Transform: Airflow, dbtCloud: AWS (primary), growing GCPBI: DomoTeam: 1 Data Engineer, 1 Data Scientist + report engineersCulture: Startup-like, high ownership, AI-forward innovationKey InitiativesCustomer 360: Unified customer data platformUser Journey Graph: Cross-channel behavioral trackingPersonalization & Recommendations: AI-driven engagement systemsTechnical Qualifications Required:5+ years of production data engineering experienceStrong experience with cloud data platforms (Snowflake preferred)Deep knowledge of data quality, governance, and architectureStrong SQL skills (distributed compute environments)Experience with Airflow, dbt, or similar toolsSolid software engineering fundamentals (APIs, data libraries)Nice to Have:Snowflake advanced features (Streams, Tasks, Snowpipe, Snowpark)Experience with MLOps, NLP, or AI/ML systemsLeadership & Culture Fit:Mentor junior engineers and promote best practicesStrong problem-solving mindset focused on automation and scalabilityEffective communicator across technical and non-technical teamsThrives in ambiguous, greenfield environmentsExcited about building AI-driven data platforms from scratch