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.
What You Bring
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 Have
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).
Perks: Why You’ll Love it Here
Generous employee discount
Summer Fridays
Casual dress code
Hybrid schedule
FOMO events (Exciting company-wide events)
Pay/Benefits Information
Actual starting pay is determined by various factors, including but not limited to relevant experience and location.
Subject to eligibility requirements, associates may receive health care benefits (including medical, vision, and dental); wellness benefits; 401(k) retirement benefits; life and disability insurance; employee stock purchase program; paid time off; paid sick leave; and parental leave and benefits.
Paid Time Off, paid sick leave, and holiday pay vary by job level and type, job location, employment classification (part-time or full-time / exempt or non-exempt), and years of service. For additional information, please click here
AEO may also provide discretionary bonuses and other incentives at its discretion.
