Enterprise Information Architect I

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.

• 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. 

• Engage with Product Managers, Business Analysts, and SMEs to translate business requirements into clear, executable solution designs and data product definitions. 

• Partner with the EDP QA / QE Lead and Quality Engineers to ensure quality is designed in from day one — including validation hooks, reconciliation strategy, and data quality expectations. 

• Collaborate with the EIM Architecture team to adopt platform standards and patterns, surface gaps or exceptions, and contribute reusable patterns back from delivery learnings. 

• Produce design assets (HLD/LLD, sequence and data flow diagrams, mapping specs) and lead solution design reviews; document key design decisions and tradeoffs in Confluence. 

• Contribute pragmatically to AI / GenAI enablement on EDP where it strengthens solution outcomes — for example, supporting metadata-driven workflows, AI-ready data product design, and consumption patterns for AI / data-agent use cases. 

• Continuously evaluate new tools and techniques on GCP and recommend practical improvements aligned to security, cost, and reliability standards. 

• Operate in an Agile / Kanban model using Jira and Confluence; deliver incremental, measurable outcomes while establishing durable patterns and standards. 

Health and Safety Requirement: Every employee is responsible for contributing to a safe and healthy workplace. Employees are expected to be active participants in health and safety by following all safety policies and procedures, reporting unsafe conditions or at-risk behaviors to leadership, and conducting work in a safe manner. Those in a leadership role are also expected to model safe behaviors, evaluate risk, and ensure that risks are reduced to acceptable levels.

• 8+ years of overall IT experience with significant hands-on delivery in modern data platforms, and 3+ years in a solution architect. 

• Strong, hands-on experience with Google Cloud Platform data services — BigQuery (modeling, optimization, cost / performance patterns), Dataflow, Cloud Composer, Dataform, and Cloud Storage. 

• Demonstrated expertise across the full data management lifecycle — conceptual, logical, and physical data modeling; source-to-target mapping; transformation design; and data product structure. 

• Strong foundation in dimensional modeling and star schemas, metric definitions, and consumption-ready data structures. 

• Strong SQL skills, including the ability to design and reason about complex queries and transformations on large data sets. 

• Working knowledge of security and access design on GCP — IAM, least-privilege, and domain / dataset-based access concepts. 

• Demonstrated ability to operate across architecture and implementation — defining a design, prototyping where needed, guiding engineers through it, and reviewing the build against intent. 

• Solid grasp of integration and pipeline patterns — batch and streaming ingestion, ELT / ETL, orchestration, error handling and retries, and observability. 

• Understanding of data privacy, security, and compliance principles (least privilege, encryption at rest / in transit, PII / PCI considerations). 

• Working knowledge of CI/CD, version control (Git), and modern Data Ops practices. 

• Strong collaboration and communication skills; able to explain design tradeoffs to both technical and non-technical stakeholders and to turn ambiguous requirements into concrete solution designs. 

• Experience in retail, consumer, or omni-channel domains (customer, product, inventory, orders, pricing, promotions, loyalty). 

• Prior work on platform modernization or EDW-to-GCP migration programs of comparable scale. 

• Familiarity with semantic layer concepts, data catalog / metadata platforms, and governance workflows. 

• Exposure to LLM-enabled or agentic tooling and patterns for AI-ready data products. 

• Working proficiency in Python for prototyping and pipeline support. 

• GCP certification, particularly Professional Data Engineer or Professional Cloud Architect. 

• Log analysis and observability experience (e.g., Cloud Logging / Monitoring, Splunk) for incident triage and root-cause analysis. 

• Highly collaborative, team-oriented environment; work closely with the EIM Architecture team, data engineers, quality engineers, product owners, and business stakeholders. 

• Agile delivery (Scrum / Kanban); use Jira for work tracking and Confluence / SharePoint for documentation. 

• Balance innovation with pragmatism; deliver incremental value while establishing durable patterns and standards on EDP for the long term. 

• Strong ownership orientation — identify gaps, propose options, drive alignment and closure on design decisions. 

L.L.Bean uses a market-based compensation approach. The anticipated starting base pay for this position is $120,200.00 - $150,200.00. Individual compensation may vary based on factors such as a candidate’s experience, qualifications, education, geographic location, skills, competencies, and proficiency for the role.

 

 

If you care about the outdoors, joining L.L.Bean is a great way to feel good about what you do. Our benefits package makes a good thing even better, with programs and perks designed to support your health and financial goals. Plus, maintaining a healthy work-life balance and re-charging outside are all part of the plan.

If your experience looks a little different from what we've identified and you think you'd be great at this role, we'd love to learn more about you!   At L.L.Bean, we believe the outdoors brings out the best in all of us.  We strive to reflect this every day in our commitments to employees and partners and in our efforts to promote belonging.