Job Title

About Costco Wholesale:Costco Wholesale is a multi-billion-dollar global retailer with warehouse club operations in eleven countries. They provide a wide selection of quality merchandise, plus the convenience of specialty departments and exclusive member services, all designed to make shopping a pleasurable experience for their members.About Costco Wholesale India:At Costco Wholesale India, we foster a collaborative space, working to support Costco Wholesale in developing innovative solutions that improve members’ experiences and make employees’ jobs easier. Our employees play a key role in driving and delivering innovation to establish IT as a core competitive advantage for Costco Wholesale. Manager - Data Engineering (MarTech)Overview:The Manager of Data Engineering at Costco is a strategic technical leader responsible for the design, development, and operationalization of data pipelines that power the /"Single Source of Truth/" for the company. You will lead a team of Data Engineers to build scalable ETL/ELT processes that support everything from clickstream analysis, purchase history, and powering a new /"One Digital Member/" strategy for member personalizationResponsibilities:Technical Skills:Lead, coach, and develop a high-performing team of Data Engineers. Conduct regular 1:1s, career development discussions, and performance reviews.Oversee the development of complex data pipelines using Costco’s GCP based implementation for the delivery of certified data setsPartner with Product Owners and Data Architects to translate business requirements (e.g., membership analytics, supply chain optimization) into technical data solutions.Guides the design data of pipelines and recommends ongoing optimization of data storage, data ingestion, data quality and orchestration.Designs, develops, and implements ETL/ELT/CDC processes using Data Build Tool (DBT) and other native GCP Services (Big Query Subscriptions, Dataproc, Dataflow, etc.)Leverages GCP services such as Big Query, Alloy DB, Spanner, Data plex, Pub/Sub, Cloud Storage, etc. to improve and speed delivery of our data products and services.Identifies, designs, and implements internal process improvements: automating manual processes, optimizing pipeline delivery and support.Identifies ways to improve data reliability, efficiency, and quality of data managementParticipate in off hours 24/7 on call support on a rotational basis8+ years in Data Engineering, with at least 3+ years in a formal leadership or management role.5+ years' experience engineering and operationalizing data pipelines with large and complex datasets.3+ years’ experience working with Big Query, Google Cloud Storage, AlloyDB and Spanner5+ years’ experience with Data Pipeline, ETL/ELT, and Data WarehousingEffective use of AI and/or LLMs to increase efficiency in deliverablesExtensive experience working with various data sources (DB2, SQL, Oracle, flat files (csv, delimited), APIs, XML, JSON)Experience implementing data integration techniques such as event/message-based integration (Kafka, Google Pub/Sub)Advanced SQL skills: solid understanding of relational databases and business data; ability to write complex SQL queries against a variety of data sources.Strong understanding of database storage concepts (data lake, relational databases, NoSQL, Graph, data warehousing).Governance & Quality: Establish and enforce standards for data quality, CI/CD, and automated testing to ensure the reliability of enterprise datasets.