Job description

Title: Manager - Data Engineering Reports To: Director - Data Engineering Location: Pittsburgh, PA or New York, NY American Eagle is a youth culture brand grounded in denim. Our purpose extends beyond making the best jeans–we embrace self expression, culture, optimism and connection. Through the brand platform Live Your Life, we empower our community to be who they want to be all while wearing the clothes that make them most confident. Get to Know the Role: We are seeking a results-driven Data Engineering Manager to lead the Consumer Data Engineering Team, specifically overseeing domains such as Customer, Digital/eCommerce, and Store Operations. You will lead a team of high-performing onshore engineers and offshore partners to build robust data products that drive operational efficiency. This role requires a blend of people leadership, project management, and deep domain expertise in retail operations to cultivate a sustainable, high-performance engineering culture. What You’ll Do: • Domain Leadership: Direct oversight of the Consumer engineering teams, ensuring technical roadmaps are aligned with business priorities like customer personalization, marketing attribution, and omnichannel engagement. • Team Management: Directly manage a team of Data Engineers, providing technical mentorship, performance management, and professional development. • Architectural Collaboration: Partner closely with the Sr. Data Architect to ensure all domain-specific pipelines align with enterprise-wide technical standards and the Medallion architecture blueprint. • Stakeholder Intake: Act as the primary technical point of contact for Consumer-side business leads, translating complex operational needs into actionable engineering requirements. • Strategic Engineering Culture: Establish and maintain best practices for code quality, documentation, and automated testing to ensure the long-term sustainability of the Consumer data ecosystem. • Product Delivery: Ensure the delivery of high-quality "Gold" layer data products within our GCP Medallion architecture. What You Bring: • Experience: 8+ years in Data Engineering with at least 2+ years of formal people management or team lead experience. • Domain Expertise: Deep understanding of Customer Data (CRM, Loyalty, Customer 360), Digital/eCommerce (web/app clickstream), Marketing Analytics (attribution, campaign performance), and Store Operations. • GCP Technical Proficiency: Hands-on experience with Google BigQuery, Cloud Composer (Airflow), and building pipelines using SQL and Python. • Modern Modeling Knowledge: Familiarity with Dimensional Modeling (Star/Snowflake) and its application within a Medallion architecture (Bronze/Silver/Gold). • Strategic Mindset: Strong problem-solving and systems-thinking skills with a proven ability to balance short-term execution with long-term platform health. • Agile Methodology: Experience running high-velocity engineering sprints and managing a backlog of data product features. Nice to Have: • 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. #LI-CH1

Requirements

Must-haves

Title: Manager - Data Engineering
Reports To: Director - Data Engineering
Location: Pittsburgh, PA or New York, NY
Domain Leadership: Direct oversight of the Consumer engineering teams, ensuring technical roadmaps are aligned with business priorities like customer personalization, marketing attribution, and omnichannel engagement.
Team Management: Directly manage a team of Data Engineers, providing technical mentorship, performance management, and professional development.
Architectural Collaboration: Partner closely with the Sr. Data Architect to ensure all domain-specific pipelines align with enterprise-wide technical standards and the Medallion architecture blueprint.
Stakeholder Intake: Act as the primary technical point of contact for Consumer-side business leads, translating complex operational needs into actionable engineering requirements.
Strategic Engineering Culture: Establish and maintain best practices for code quality, documentation, and automated testing to ensure the long-term sustainability of the Consumer data ecosystem.
Product Delivery: Ensure the delivery of high-quality "Gold" layer data products within our GCP Medallion architecture.
Experience: 8+ years in Data Engineering with at least 2+ years of formal people management or team lead experience.
Domain Expertise: Deep understanding of Customer Data (CRM, Loyalty, Customer 360), Digital/eCommerce (web/app clickstream), Marketing Analytics (attribution, campaign performance), and Store Operations.
GCP Technical Proficiency: Hands-on experience with Google BigQuery, Cloud Composer (Airflow), and building pipelines using SQL and Python.
Modern Modeling Knowledge: Familiarity with Dimensional Modeling (Star/Snowflake) and its application within a Medallion architecture (Bronze/Silver/Gold).
Strategic Mindset: Strong problem-solving and systems-thinking skills with a proven ability to balance short-term execution with long-term platform health.
Agile Methodology: Experience running high-velocity engineering sprints and managing a backlog of data product features.
Actual starting pay is determined by various factors, including but not limited to relevant experience and location.
AEO may also provide discretionary bonuses and other incentives at its discretion.

Nice-to-haves

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
Summer Fridays
Casual dress code
Hybrid schedule
FOMO events (Exciting company-wide events)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gcpsqlpythonagileai

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness

Professional Development