Enterprise Information Architect I - L.L. Bean, Inc.

At L.L.Bean, we believe the outdoors brings out the best in all of us. We are committed to fostering a culture of belonging and creating safe, inclusive spaces where everyone feels welcome—both here and Outside. We value individual differences and are dedicated to maintaining an inclusive work environment where everyone can bring the best of their experience and talents and truly thrive.

Position Purpose:

We're looking for a EIM Architect who will be fully dedicated to our Enterprise Data Platform (EDP) — a modern, GCP-native platform that supports both the migration of workloads from our legacy on-premises EDW and the build-out of net-new enterprise data products across marketing, customer, supply chain, and other retail business domains. This is a hands-on, senior role designing end-to-end data solutions across ingestion, transformation, and consumption layers, and partnering shoulder-to-shoulder with data engineers, product, and business partners to deliver trustworthy, scalable data products.

You'll operate at the intersection of architecture and delivery — translating business needs into conceptual, logical, and physical designs, making pragmatic GCP service decisions, and helping teams implement solutions that scale. You'll partner closely with our EIM Architecture team to adopt and evolve platform standards, and act as a durable technical leader on EDP for the years ahead.

Location: In USA, We welcome the opportunity for this role to be hybrid at our headquarters in Freeport, ME, or approved remote states: Colorado, Connecticut, Florida, Georgia, Illinois, Kansas, Maine, Maryland, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New York, North Carolina, South Carolina, Ohio, Pennsylvania, Rhode Island, Utah, Vermont, Virginia, Wisconsin.

What You'll Do (Responsibilities)

Design end-to-end data solutions on EDP — spanning ingestion, transformation, and consumption — for both migration waves and net-new use cases, taking designs from conceptual through logical and physical models.

Define source-to-target mappings and transformation designs, including handling of data types, nulls, defaults, slowly changing dimensions, and business rule logic.

Make hands-on GCP service selection and design decisions across BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage — balancing performance, cost, security, and operability.

Design dimensional and analytics-ready data models (star schemas, fact/dimension structures) that align with downstream BI and consumption needs.

Apply security, access, and least-privilege design principles at the dataset and domain level in line with platform standards.

Partner closely with Tech Leads and Data Engineers — providing hands-on design guidance, unblocking tradeoff decisions, and reviewing implementation against the agreed design.