Sr. Data & Analytics Architect

OverviewAs Senior Data & Analytics Architect, you will lead the design and implementation of scalable data platforms and analytics solutions to empower strategic decision-making and operational efficiency. You will translate business needs into robust architectures that enable AI/ML capabilities across the enterprise, working with cross-functional teams to deliver timely, value-driven data solutions. Your leadership will guide cloud-native data estates, real-time pipelines, and governance frameworks that support innovation. This role offers impact at scale within Grocery Outlet's technology-focused culture.

Compensation / BenefitsBase salaryAnnual bonus programEquity401(k) Profit SharingMedical, Dental, Vision & MoreResponsibilitiesDesign and implement enterprise-scale data architectures supporting analytics, ML, and AI applicationsArchitect modern data platforms (data lakes, lakehouses, warehouses, real-time pipelines)Define AI/ML solution architecture including model training, deployment, monitoring, and governanceDesign and support dashboard development using PowerBI, Databricks, etc.Lead architecture for data and AI workloads on cloud platforms (AWS, Azure, GCP)Implement scalable pipelines using Spark, Databricks or similarDevelop AI-driven solutions including predictive analytics, NLP, and recommender systemsSupport MLOps and AI lifecycle management (deployment, monitoring, versioning)Design integrations between data platforms, operational systems, and AI servicesDefine data governance, security, and compliance standardsCollaborate with business leaders to translate problems into technical solutionsMentor engineers and architects; establish standards and best practicesKey requirements10+ years in data engineering, analytics, or platform architecture5+ years designing cloud-based data platforms and AI/ML solutionsStrong expertise with data patterns (data lake, lakehouse, warehouse)Experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)Hands-on with big data tech (Spark, Databricks, Hadoop ecosystem)Strong SQL, Python, and distributed data systems knowledgeExperience implementing MLOps pipelines and model lifecycle managementExcellent communication and stakeholder managementExperience with Generative AI and LLM-based applicationsKnowledge of data governance platforms and metadata managementIndustry experience in retail, e-commerce, finance, or supply chainRelevant certifications (AWS/Azure/GCP Architect, Databricks, Snowflake)Knowledge of SAP systems and data structures is a plusstrong communicationstakeholder managementleadership and mentorshipdata architecture patterns (data lake, lakehouse, warehouse)AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)big data technologies (Spark, Databricks, Hadoop)