EY Data Engineer - Industrials & Energy Sector 

United States, New York, New York 

73182608

a Senior Manager in Data Engineering focusing on helping our clients with future forward data strategy and data management inthe advanced manufacturing sector, including vehicle automation, connectivity, electrification, and enterprise AIThis leadership role requires a seasoned professional with a strong background in data engineering to guide the development of cloud-based solutions, drive pre-sales efforts, and manage complex projects that meet organizational goals.

Your Key Responsibilities

Strategic Oversight

Cloud Solutions Leadership

Solution Recommendation:Utilize your strong background to recommend and lead cloud-based and data engineering solutions, addressing complex technical challenges and ensuring optimal performance.

Pre-Sales and RFPs: Engage in pre-sales activities and contribute to RFP responses by developing and articulating advanced data engineering solutions that address client needs and demonstrate the value of our offerings.

AI/ML and Advanced Analytics

Data Requirements and Validation: Define data requirements, manage the ingestion of structured and unstructured data, and validate data using tools and methodologies in a Big Data environment.

Technical Leadership: Evaluate, implement, and deploy emerging tools and processes to enhance data engineering capabilities. Develop and deliver communication and education plans on data engineering standards and practices.

Digital and Cloud Modernization: Lead digital transformation and cloud modernization efforts, leveraging cloud-native technologies and practices to improve data engineering solutions and processes.

Skills and Attributes for Success

Cloud Solutions Expertise: Strong background in designing and implementing cloud-based data solutions using AWS, Azure, Databricks, and other relevant cloud technologies.

AI/ML Integration: Experience with AI/ML technologies, including machine learning, large language models (LLM), and integration of AI/ML capabilities into data engineering workflows.

Data Engineering Proficiency: Extensive knowledge of data engineering principles, including building and optimizing data pipelines, and managing data architectures.

Technical Skills: Proficiency in programming languages such as Python and Pyspark, and experience with distributed data technologies and API development.

Pre-Sales and Proposal Management: Proven experience in pre-sales activities and contributing to RFP responses, with a track record of developing solutions that align with client requirements.

Leadership and Mentorship

Digital and Cloud Modernization: Experience in leading digital transformation and cloud modernization initiatives, leveraging cloud-native technologies and practices.

Problem Solving

To Qualify for the Role You Must Have

Educational Background: A bachelor’s degree or higher in Engineering, Computer Science, Data Science, or a related field.

: Minimum 8 years of experience in data engineering, including significant experience in managing large-scale data projects and leading technical teams.

Proven Track Record: Demonstrated ability to recommend and implement complex data solutions, manage data pipelines, and drive data quality and reconciliation.

Technical Skills: Experience with AWS, Azure, Databricks, Python, Pyspark, API development, and cloud modernization practices.

Organizational Skills

Ideally, you’ll also have

• Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
• Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.