Director, Data Engineering

Macy's•Johns Creek, GA

About The Position

The Director, Data Engineering leads the engineering and operation of enterprise-grade data pipelines that make data trusted and reliable. This role involves development of new data capabilities and the ongoing support, measurement, and improvement of existing platforms, with a strong focus on scalability, resilience, and reducing technical debt. By simplifying data flows and accelerating delivery, the Director enables analytics, AI, and product teams to move faster and helps the business focus on what’s next.

Requirements

Data Pipeline Automation: Designs and scales automated ETL/ELT pipelines using enterprise-grade tools and frameworks.
Big Data Technologies: Leverages distributed processing platforms (i.e Hadoop) to manage large, complex datasets.
Metadata & Data Management: Implements metadata and data management solutions that improve discovery and data quality.
Data Warehousing: Builds and operates enterprise-grade data warehouses across cloud and on-prem environments.
10+ years of experience designing, scaling, and operating enterprise-grade data engineering platforms in big-data environments.
3+ years in a People Leader role.
An ongoing learner that influences others to think innovatively.
Ability to clearly and effectively communicate complex issues and insights to a variety of stakeholders, including non-experts.
Passionate about solving customer and business problems.
Regularly required to sit, talk, hear; use hands/fingers to touch, handle, and feel. Occasionally required to move about the workplace and reach with hands and arms. Requires close vision.
Able to work a flexible schedule based on department and company needs.

Nice To Haves

Agentic AI automation within Data Engineering pipelines preferred.

Responsibilities

Lead, mentor, and coach managers and individual contributors, raising the talent bar across the Enterprise Data & Analytics Team and promoting a culture of continuous improvement.
Act as a trusted partner to stakeholders, ensuring alignment between business objectives and insights strategy.
Maintain, streamline, and enhance enterprise data pipelines and data landscapes supporting priority analytics and data science use cases.
Institute processes ensuring data quality, consistency, curation, and the establishment of authoritative “single source of truth” datasets.
Conduct and oversee data transformations, cleansing, classification, and “last mile” preparation to enable analytics and modeling at scale.
Partner with BI & Data Science teams to understand data sourcing and formatting needs that accelerate usecase development.
Collaborate with Technology teams to modernize and futureproof tools, architecture, codebases, and data platforms.
Ensure compliance with legal, privacy, and security standards in partnership with Legal, Privacy, and Data Governance teams.
Create and foster a community of practice for data and analytics across the enterprise.
Drive change management and user adoption of enterprise data repositories and standardized pipelines.
Build agility in identifying and remediating data issues to improve reliability and speed.
Stay current on emerging trends and Agentic AI technologies in data analytics.

Benefits

competitive pay and benefits
comprehensive health and wellness coverage
401(k) match
paid time off
eight paid holidays
continuous learning and leadership development
Merchandise discounts
Performance-based incentives
Annual merit review
Employee Assistance Program with mental health counseling and legal/financial advice
Tuition reimbursement