Data Engineer and Analytics Platform Manager - Assistant Director

EY•Hartford, DC

2d•$124,400 - $264,400

About The Position

As an Assistant Director – Data Engineering & Analytics Platforms, you will help shape enterprise data, analytics and AI capabilities in partnership with business leaders, architects and engineering teams. You will establish technical direction, deliver modern data platforms and develop solutions that create measurable business value. You will help lead the design and delivery of advanced data and AI solutions using Microsoft Fabric, Azure Databricks, cloud platforms and emerging AI technologies. The role includes guiding architecture decisions, mentoring engineering teams, removing delivery barriers and establishing practices for secure, scalable and high-performing solutions. You will also help advance adoption of generative AI, intelligent agents and AI-powered analytics, influencing the evolution of AI agent architecture, enterprise data platforms and next-generation analytics capabilities. The role involves leading technical workstreams and multidisciplinary teams through solution design, development, testing, deployment and production support, including coordination with geographically distributed teams and onshore/offshore transitions.

Requirements

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, analytics engineering or a related technology-delivery field.
Demonstrated experience providing technical leadership to development teams and guiding architecture and solution-design decisions.
Hands-on experience designing, developing or delivering enterprise data and analytics solutions using Azure Databricks or Microsoft Fabric; experience with at least one is required.
Strong knowledge of data ingestion, transformation, orchestration, integration, modelling, testing, monitoring and production support.
Experience reviewing technical designs, platform integrations, data pipelines and analytics solutions.
Experience managing technical risks, dependencies, governance requirements, competing priorities and delivery timelines.
Experience leading technical workstreams or multidisciplinary teams through requirements, design, development, testing, deployment and production support.
Experience communicating technical concepts, risks and recommendations to technical and non-technical stakeholders.
Experience leading or supporting onshore and offshore delivery models, knowledge-transfer activities and operational handoffs.
Strong technical leadership, problem-solving, decision-making, stakeholder-management and communication skills.
Ability to balance strategic thinking with hands-on technical leadership, manage ambiguity and organizational change, and collaborate across functions, business areas, geographies and time zones.
Ability to review technical solutions, identify risks and recommend practical improvements.
Proven ability to coach and mentor technical professionals.

Nice To Haves

Experience with Azure AI Foundry.
Experience designing, developing or supporting AI and data agents using Databricks Genie, Microsoft Fabric Data Agents or comparable agent-based technologies.
Experience delivering generative AI, conversational analytics, natural-language data experiences or AI-enabled business insights in an enterprise environment.
Relevant Microsoft Azure, Databricks or Microsoft Fabric certifications.

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 meet business, security, scalability, quality and operational requirements.
Lead technical workstreams 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 governance and quality controls.
Identify and remove technical and delivery barriers and help teams resolve complex issues.
Coach and mentor team members, strengthen technical capabilities, promote knowledge sharing and encourage consistent engineering practices.
Communicate technical risks, options and recommendations 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 ownership, communication channels, escalation processes and quality expectations across geographically distributed teams.