Data Engineer - Industrials & Energy Sector - Senior Manager - Consulting - Location Open

Ernst & Young - Trenton, NJ

Full-time - Senior

Trenton, NJ

Professional, Scientific, and Technical Services

About the position

The Data Engineer - Industrials & Energy Sector - Senior Manager position at EY is a leadership role focused on guiding clients in the advanced manufacturing sector through data strategy and management. This role involves overseeing the development of cloud-based solutions, managing complex projects, and driving pre-sales efforts to meet organizational goals. The position requires a seasoned professional with a strong background in data engineering, particularly in areas such as vehicle automation, connectivity, electrification, and enterprise AI.

Responsibilities

• Lead the strategic design and implementation of data engineering initiatives.
• Oversee the design and maintenance of scalable data pipelines and architectures using cloud platforms such as AWS, Azure, and Databricks.
• Utilize expertise to recommend and lead cloud-based and data engineering solutions.
• Engage in pre-sales activities and contribute to RFP responses by developing advanced data engineering solutions.
• Collaborate with AI/ML engineers to design and implement data solutions that support machine learning and advanced analytics.
• Define data requirements, manage the ingestion of structured and unstructured data, and validate data in a Big Data environment.
• Implement processes for data reconciliation and quality monitoring.
• Evaluate, implement, and deploy emerging tools and processes to enhance data engineering capabilities.
• Lead digital transformation and cloud modernization efforts.
• Mentor and lead a team of data engineers, fostering a culture of innovation and continuous improvement.
• Partner with Business Analytics, Solution Architects, Data Scientists, and AI/ML engineers to design and deliver data solutions.

Requirements

• Strong background in designing and implementing cloud-based data solutions using AWS, Azure, and Databricks.
• Experience with AI/ML technologies, including machine learning and large language models (LLM).
• Extensive knowledge of data engineering principles and ETL best practices.
• Proven ability to manage complex projects and lead teams effectively.

Nice-to-haves

• Experience in the advanced manufacturing sector.
• Familiarity with data quality and reconciliation processes.
• Knowledge of digital transformation and cloud modernization practices.

Benefits

• Comprehensive health insurance coverage.
• 401(k) retirement savings plan with company matching.
• Flexible work hours and remote work options.
• Professional development and learning opportunities.