Data Engineering - Manager- MarTech

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 personalization
Responsibilities:
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 Costcos GCP based implementation for the delivery of certified data sets
• Partner 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 management
• Participate in off hours 24/7 on call support on a rotational basis
• 8+ 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 Spanner
• 5+ years experience with Data Pipeline, ETL/ELT, and Data Warehousing
• Effective use of AI and/or LLMs to increase efficiency in deliverables
• Extensive 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.