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

Ernst & Young - Secaucus, NJ

Full-time - Senior

Secaucus, NJ

Professional, Scientific, and Technical Services

About the position

The Senior Data Engineer at EY will be responsible for ingesting, building, and supporting large-scale data architectures that serve multiple downstream systems and business users within the Industrials & Energy sector. This role involves collaborating with various teams to ensure data quality, troubleshooting, and the development of scalable data pipelines using AWS technologies. The position emphasizes the importance of data integrity and aims to deliver insights that align with business objectives.

Responsibilities

• Design, develop, optimize, and maintain data architecture and pipelines adhering to ETL principles and business goals.
• Develop and maintain scalable data pipelines and build new integrations using AWS native technologies.
• Define data requirements, gather and mine large-scale structured and unstructured data, and validate data using various tools in a Big Data Environment.
• Support standardization, customization, and ad hoc data analysis, and develop mechanisms to ingest, analyze, validate, normalize, and clean data.
• Write unit/integration/performance test scripts and perform data analysis to troubleshoot data-related issues.
• Implement processes and systems to drive data reconciliation and monitor data quality, ensuring production data is accurate and available.
• Lead the evaluation, implementation, and deployment of emerging tools and processes for analytic data engineering.
• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
• Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
• Solve complex data problems to deliver insights that help achieve business objectives.
• Implement statistical data quality procedures on new data sources.

Requirements

• Bachelor's degree in Engineering, Computer Science, Data Science, or related field.
• 5+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development.
• Experience designing, building, implementing, and maintaining data and system integrations using dimensional data modeling and ETL pipeline optimization.
• Proven track record of designing and implementing complex data solutions.
• Demonstrated understanding and experience using Data Engineering Programming Languages (i.e., Python).

Nice-to-haves

• Experience with distributed data processing frameworks (e.g., Apache Spark, Hadoop).
• Familiarity with machine learning and AI concepts.
• Knowledge of data visualization tools and techniques.

Benefits

• Inclusive culture and support for career development.
• Opportunities for professional growth and learning.
• Access to advanced technology and resources.