Manager - Data Engineering

About 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.

Responsibilities

• Direct oversight of the Consumer engineering teams, ensuring technical roadmaps are aligned with business priorities like customer personalization, marketing attribution, and omnichannel engagement.
• Directly manage a team of Data Engineers, providing technical mentorship, performance management, and professional development.
• Partner closely with the Sr. Data Architect to ensure all domain-specific pipelines align with enterprise-wide technical standards and the Medallion architecture blueprint.
• Act as the primary technical point of contact for Consumer-side business leads, translating complex operational needs into actionable engineering requirements.
• Establish and maintain best practices for code quality, documentation, and automated testing to ensure the long-term sustainability of the Consumer data ecosystem.
• Ensure the delivery of high-quality "Gold" layer data products within our GCP Medallion architecture.

Requirements

• 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.

Qualifications

• Nice To Have: 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).

Skills

• Strong problem-solving and systems-thinking skills.
• Familiarity with Dimensional Modeling (Star/Snowflake).
• Hands-on experience with Google BigQuery, Cloud Composer (Airflow), and building pipelines using SQL and Python.
• Proven ability to balance short-term execution with long-term platform health.
• Experience running high-velocity engineering sprints and managing a backlog of data product features.
• Familiarity with Generative AI technologies (e.g., using LLMs for SQL generation, automated metadata documentation, or synthetic data creation).

Benefits

• Generous employee discount.
• Summer Fridays.
• Casual dress code.
• Hybrid schedule.
• FOMO events (Exciting company-wide events).

Pay

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.

Schedule

Full time.

Location

Pittsburgh, PA, United States.