Data Engineer and Analytics Platform Manager - Assistant Director

Location:

Dallas, Akron, Alpharetta, Arlington, Atlanta, Baltimore, Boca Raton, Boston, Buffalo, Charleston, Charlotte, Chattanooga, Cincinnati, Cleveland, Detroit, Grand Rapids, Grandview Heights, Greenville, Hartford, Hoboken, Indianapolis, Iselin, Jacksonville, Jericho, Louisville, Manayunk, McLean, Miami, New York, Orlando, Philadelphia, Pittsburgh, Providence, Raleigh, Richmond, Rochester, Stamford, Tallahassee, Tampa, Toledo, Washington, Austin, Baton Rouge, Birmingham, Chicago, Des Moines, Fort Worth, Houston, Huntsville, Jackson, Kansas City, Memphis, Milwaukee, Minneapolis, Nashville, New Orleans, Oklahoma City, Rogers, San Antonio, St.

Louis, Tulsa, Wichita

At EY, we're all in to shape your future with confidence.

We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.  Join EY and help to build a better working world.

** The opportunity*
* As an Assistant Director - Data Engineering & Analytics Platforms, you'll play a role in shaping enterprise data, analytics and AI capabilities. You'll partner with business leaders, architects and engineering teams to establish technical direction, deliver modern data platforms and develop solutions that create measurable business value.

You'll help lead the design and delivery of advanced data and AI solutions using Microsoft Fabric, Azure Databricks, cloud platforms and emerging AI technologies. You'll guide architecture decisions, mentor engineering teams, remove delivery barriers and establish practices that support secure, scalable and high-performing solutions.

You'll also help advance the organization's adoption of generative AI, intelligent agents and AI-powered analytics. Working with stakeholders, delivery teams and technical leaders, you'll influence the evolution of AI agent architecture, enterprise data platforms and next-generation analytics capabilities.

** Your key responsibilities*
* + Provide technical leadership for enterprise data, analytics and AI platform initiatives, from requirements and solution design through deployment and production support.

+ Guide architecture and solution-design decisions to ensure solutions meet business, security, scalability, quality and operational requirements.

+ Lead technical work streams and multidisciplinary teams through design, development, testing, deployment and ongoing support.

+ Review technical designs, data pipelines, platform integrations and analytics solutions for reliability, scalability, maintainability and performance.

+ Manage technical risks, dependencies, competing priorities and delivery timelines while maintaining appropriate governance and quality controls.

+ Identify and remove technical and delivery barriers, helping teams resolve complex issues.

+ Coach and mentor team members, strengthen technical capabilities and promote knowledge sharing and consistent engineering practices.

+ Communicate technical risks, options and recommendations clearly to technical and non-technical stakeholders.

+ Lead or support onshore and offshore transitions, including readiness assessments, knowledge transfer, documentation, handoffs and post-transition stabilization.

+ Establish clear ownership, communication channels, escalation processes and quality expectations across geographically distributed teams.

** Skills and attributes for success*
* + Strong technical leadership skills, with the ability to influence direction and drive delivery across multiple teams.

+ Deep understanding of modern data engineering, analytics and cloud-platform concepts.

+ Ability to balance strategic thinking with practical, hands-on technical leadership.

+ Strong problem-solving and decision-making skills in complex technical environments.

+ Ability to review technical solutions, identify risks and recommend practical improvements.

+ Proven ability to coach and mentor technical professionals.

+ Strong stakeholder-management and communication skills.

+ Ability to manage ambiguity, competing priorities and organizational change.

+ Collaborative approach with the ability to work effectively across functions, business areas, geographies and time zones.

** To qualify for the role, you must have*
* + A bachelor's degree in Computer Science or a related technology discipline, such as Software Engineering, Computer Engineering, Information Systems, Data Engineering, Data Science or Information Technology.

+ 8 to 12 years of progressive professional experience in data engineering, data platforms,…