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Grocery Outlet

Data Solution Architect

Grocery Outlet, Emeryville, California, United States, 94608


About Grocery Outlet: Our Mission:

Touching lives for the better Our Vision:

Touching lives by being the first choice for bargain-minded consumers in the U.S. Our Values & Behaviors:

Achievement, Diversity, Entrepreneurship, Family, Fun, Integrity & Service About the Team: Our IT team's mission is to push the boundaries of technology with the intention of going above and beyond to aid stores and customers and deliver timely solutions to benefit all members of Grocery Outlet. Our team consists of problem solvers and go-getters who are dedicated to being service-oriented and solving important problems.

About the Role: The Data Solution Architect is responsible for designing, developing, and supporting Data Platform primarily in Sales, Inventory, Planning & Ecommerce Data Domains / In this role, you will ensure the highest data integrity, governance, and service to internal and external customers. You will be building highly scalable data pipelines and Data marts using Python and Spark & SQL, strengthen data governance, and increase data value by deploying user-friendly processes and system tools and simplifying data architecture. This role reports to the Sr Enterprise Data Architect.

Responsibilities Include:

Collaborate closely with product managers and other engineers to understand business priorities, business workflows, and architect data solutions. You will go well beyond bespoke tables to solve one-off use cases. You will model the enterprise business lines with robust, crisp documentation with target gold tables and pipeline flow. Develop, deploy, and manage scalable pipelines on Databricks and build data models/data marts Investigate and leverage Databricks' capabilities to implement real-time data processing and streaming, potentially using Spark Streaming, Online Tables, Delta Live Tables. Contribute and maintain the high quality of the code base with comprehensive data observability, metadata standards, and best practices. Hands on Build Data Pipelines using Python, Pyspak, SQL Partner with data science and reporting teams to understand data requirements and translate them into models. Mentor Junior Data Engineers as the team grows. Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices. Empower internal teams by providing communication on architecture, target gold tables, execution plans, releases and training. Experience of building Datawarehouse and lake house data integration, reporting & analytics projects in cloud environment Experience of implementing large scale solutions involving ETL/Data Ingestion/Data Integration, Business Intelligence, Reports, Dashboards, and analytics components Experience of defining/implementing key data management frameworks such as data quality, metadata management, master/reference data management, data governance, data security, etc. using standard enterprise tools e.g., Azure Purview, Databricks Unity Catalog etc. Experience of development on GCP /AWS/Azure Databricks platform using Lakehouse architecture and utilizing Databricks tools/utilities such as Delta Lake, Autoloader, Delta Live Tables, Unity Catalog, Orchestration, Analytics/Machine Learning, etc. Ability to understand On-prem and cloud-based workloads based on requirements and constraints and provide suggestions for best possible solution Ability to work with various Business and IT stakeholders in establishing the Architecture, Design, and implementation artifacts Ability to effectively communicate, explain and present Architecture and design to IT leaders and other stakeholders About The Pay:

Base Salary Range: $110,000 - $130,000 Annually Annual Bonus Program Equity 401(k) Profit Sharing Medical, Dental, Vision & More! Final compensation will be determined based upon experience and skills and may vary based on location. About You:

Bachelor's or master's degree in computer science 7+ years of industry experience in Data Engineering 2+ years of proven experience at the data architect level leading modeling. 5+ years of industry experience in SQL, Spark, and/or other programming languages. 2+ years of experience with Databricks environment Nice to have: Familiarity with real-time ML systems within Databricks will be very beneficial Excellent communication skills to work effectively with business stakeholders.

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