The Senior Data Engineer role at EY focuses on designing and building analytics solutions that deliver significant business value. The position requires expertise in cloud data engineering, particularly with Databricks, and involves collaboration with various stakeholders to ensure alignment between technical requirements and business needs. The role is part of a diverse team dedicated to transforming data into actionable insights while maintaining data quality and security. This position offers opportunities for professional growth and exposure to cutting-edge technologies in a flexible work environment.

• A Bachelor's degree in Computer Science, Engineering, or a related field is required, with a Master's degree preferred.
• Typically, 2 to 4 years of relevant experience in data engineering, with a focus on cloud data solutions.
• 5+ years of experience in data engineering, specifically with Databricks and Spark for big data processing.
• Proven experience in at least two end-to-end data engineering implementations.
• Strong programming skills in languages such as Python, Scala, or SQL.

• Design and build scalable on-premises or cloud data architecture.
• Analyze business requirements and translate them into technical specifications.
• Optimize data flows for target data platform designs.
• Develop and implement data engineering solutions using Databricks on cloud platforms.
• Collaborate with clients to understand their data needs and provide tailored solutions.
• Lead end-to-end data pipeline development, including data ingestion, transformation, and storage.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Provide technical guidance and mentorship to junior data engineers and team members.
• Communicate effectively with stakeholders to convey complex data concepts.
• Manage client relationships and expectations, ensuring high levels of satisfaction.

• Ernst & Young (EY) offers a comprehensive and competitive benefits package designed to support the well-being of its employees across various dimensions.