Data Architect

American Eagle Outfitters•Pittsburgh, PA

9h•Hybrid

About The Position

American Eagle is seeking an experienced Data Architect to lead the design and implementation of their enterprise data architecture and ETL frameworks, supporting a modern data warehouse in Google Cloud Platform (GCP). This pivotal role involves shaping the data strategy, ensuring scalable, reliable, and secure solutions that empower business users and analysts to deliver actionable insights. The Data Architect will collaborate closely with business stakeholders, product managers, and the business intelligence team to enable strategic analytics and decision-making across the organization, sitting at the intersection of architecture, engineering, and business.

Requirements

Experience: 10+ years in data engineering, data architecture, or data analytics roles, with a minimum of 3 years specifically dedicated to a Data Architect position. Candidates must demonstrate a proven history of designing and delivering high-performance, enterprise-scale data strategies that bridge the gap between technical infrastructure and strategic business outcomes.
Enterprise Data Modeling: Expertise in designing and implementing enterprise data warehouses, including star/snowflake schemas and dimensional modeling techniques in a Medallion architecture.
Modern Architecture Standards: Proven experience implementing Lakehouse patterns (specifically using BigQuery and open table formats like Iceberg), Data Mesh (domain-driven design), and real-time streaming architectures.
GCP Ecosystem: Strong expertise in Google Cloud Platform, specifically BigQuery, Cloud Composer (Airflow), Dataflow, Pub/Sub, Cloud Storage, Slot Reservations/Workload Management.
Languages: Expert-level SQL is required; Python proficiency is a strong plus for custom operators and advanced data processing.
Governance: Solid understanding of data governance, metadata management, security, and compliance in cloud environments.
Platform Thinking & Strategy: Proven ability to balance immediate business delivery with long-term architectural health; a strategic thinker who can navigate complex stakeholder requirements to build scalable, future-proof data platforms.
BI Tooling: Experience working with BI tools (e.g., Tableau, Looker, AtScale, Databricks) to support self-service and enterprise reporting.
Communication: Ability to engage with both technical and non-technical stakeholders to translate complex requirements into impactful solutions.

Nice To Haves

Industry Knowledge: Background in the retail industry or high-volume transactional environments.
Emerging Technology: Familiarity with or vision for integrating Generative AI into data engineering workflows (e.g., using LLMs for SQL generation, automated metadata documentation, or synthetic data creation).

Responsibilities

Architectural Blueprinting: Design and implement scalable data architecture, pipelines, and modeling strategies that power our enterprise data warehouse on GCP (BigQuery).
ETL/ELT Ownership: Own the end-to-end ETL/ELT architecture, including ingestion, transformation, modeling, and orchestration.
Business Collaboration: Partner with business leaders and the BI team to translate strategic goals into high-quality data products and analytical solutions.
Governance & Integrity: Ensure data integrity and security by adhering to and upholding data governance, quality standards, and architectural best practices.
Innovation & Modernization: Drive modernization efforts by researching, evaluating, and implementing emerging technologies and tools across the data ecosystem.
Technical Mentorship: Serve as a technical mentor and guide to data engineers and cross-functional teams.
Platform Planning: Participate in data platform roadmap planning, vendor evaluations, and tool selection.
Efficiency: Promote reusable patterns, modular design, and automation wherever possible to ensure long-term scalability.