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.
Locations (20)
Freeport, Maine, United States
Colorado, United States
Connecticut, United States
Florida, United States
Georgia, United States
Illinois, United States
Show all 20 locations
Kansas, United States
Maine, United States
Maryland, United States
Massachusetts, United States
Michigan, United States
Minnesota, United States
Compensation
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.
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.
Requirements
Bachelor's degree in a relevant field or equivalent work experience.
Nice to have: Experience in retail, consumer, or omni-channel domains
Nice to have: Prior work on platform modernization or EDW-to-GCP migration
Partner with business stakeholders to frame problems, define success metrics, and translate business needs into analytical and data science solutions.
Perform exploratory data analysis, statistical analysis, hypothesis testing, and experimentation to identify patterns, drivers, and opportunities.
Design, develop, evaluate, and refine machine learning and statistical models for use cases such as forecasting, classification, segmentation, and anomaly detection.
Apply appropriate validation methods; assess model performance and limitations; and communicate uncertainty, assumptions, and trade-offs.
Prepare, transform, and integrate structured, semi-structured, and unstructured data. Develop reusable features and analytical datasets using Python and SQL.
Requirements
Bachelor’s or master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
Build and strengthen data pipelines that power the advertising operation, managing ELT workflows, data warehousing, and automation within a GCP-native stack.
Compensation
Base Salary: $90,000 - $120,000 CAD
Responsibilities
Build and maintain production ELT pipelines ingesting data from Google Ads, Meta Ads, and Microsoft/Bing Ads APIs into BigQuery
Own reliable Bronze layer ingestion with audit trails
Extend and maintain API connectors (REST/OAuth2) within Cloud Run patterns
As a Google Data & AI Engineer (Senior Analyst), you will build and operate data pipelines, analytics, and ML/GenAI components on Google Cloud as a core member of a delivery team.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Build, test, and deploy data pipelines, transformations, dashboards, and ML/GenAI components on Google Cloud, from requirements through production support.
Participate in client discussions, clarify requirements, and communicate progress and risks clearly to leads and stakeholders.
Write clean, tested, documented code; participate in peer reviews; and monitor pipelines and models to resolve data quality and performance issues.
Apply DataOps/MLOps practices, CI/CD, and Infrastructure as Code (Terraform) within an Agile framework, and estimate your own tasks.
Contribute to reusable assets and accelerators, support junior team members, and keep building Google Cloud skills and certifications.
Build and operate data pipelines, analytics, and ML/GenAI components on Google Cloud as a core member of a delivery team.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Build, test, and deploy data pipelines, transformations, dashboards, and ML/GenAI components on Google Cloud, from requirements through production support.
Participate in client discussions, clarify requirements, and communicate progress and risks clearly to leads and stakeholders.
Write clean, tested, documented code; participate in peer reviews; and monitor pipelines and models to resolve data quality and performance issues.
Apply DataOps/MLOps practices, CI/CD, and Infrastructure as Code (Terraform) within an Agile framework, and estimate your own tasks.
Contribute to reusable assets and accelerators, support junior team members, and keep building Google Cloud skills and certifications.
Requirements
AGBG Google Data & AI Engineer - Specialist (Lead)
L9 Specialist who leads client-facing delivery of data, analytics, and AI solutions on Google Cloud, with deep GCP product expertise and domain depth in one or more of Data Platform Modernization, Analytics & BI, Generative & Agentic AI, or Customer 360.
Responsibilities
Design, build, test, and deploy complex data pipelines, analytics, and ML/GenAI solutions on Google Cloud, working across the entire delivery lifecycle from requirements gathering to production support.
Work directly with clients to understand business and data challenges, translate requirements into technical designs, and act as a technical advisor for the client throughout the project.
Lead and mentor on-shore and off-shore engineers, conduct design and code reviews, and collaborate with cross-functional stakeholders to ensure alignment and delivery excellence.
Apply DataOps/MLOps practices and Infrastructure as Code (Terraform) within an Agile framework to deliver high-quality solutions at pace.
Build accelerators, reference architectures, and POVs that make Google Data & AI delivery repeatable and tied to measurable outcomes.
Requirements
Nice to have: Java
Nice to have: Scala
Nice to have: Apache Beam
Nice to have: Google Cloud Professional Data Engineer certification
Nice to have: Google Cloud Professional Machine Learning certification
Build and operate data pipelines, analytics, and ML/GenAI components on Google Cloud as a core member of a delivery team.
Locations (2)
Bengaluru, Karnataka, India
India
Responsibilities
Build, test, and deploy data pipelines, transformations, dashboards, and ML/GenAI components on Google Cloud, from requirements through production support.
Participate in client discussions, clarify requirements, and communicate progress and risks clearly to leads and stakeholders.
Write clean, tested, documented code; participate in peer reviews; and monitor pipelines and models to resolve data quality and performance issues.
Apply DataOps/MLOps practices, CI/CD, and Infrastructure as Code (Terraform) within an Agile framework, and estimate your own tasks.
Contribute to reusable assets and accelerators, support junior team members, and keep building Google Cloud skills and certifications.
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