EY - GDS Consulting - AI And DATA -Snowflake - Senior

Core Responsibilities of a Data Engineer in D&A

Data Pipeline Design & Development

• Data Engineers are responsible for designing and building robust, scalable, and high-quality data pipelines that support analytics and reporting needs. This includes:
• ETL/ELT development using tools like Azure Data Factory, Databricks, and Snowflake.
• Integration of structured and unstructured data from various sources into data lakes and warehouses.

Cloud Platform Engineering

• They operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.
• Manage environments, performance tuning, and configuration for cloud-native data solutions.

Data Modeling & Architecture

• Apply dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.
• Collaborate with solution architects and analysts to ensure models meet business needs.

Data Governance & Security

• Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
• Implement data masking, access controls, and metadata management for sensitive datasets.

Collaboration & Agile Delivery

• Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.
• Participate in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.

Mentorship & Talent Development

Help business users understand and leverage analytics tools effectively.

 Key Skills Required

• Programming: Python, SQL, Spark
• Cloud Platforms: Azure, AWS, Snowflake
• Data Tools: DBT, Erwin Data Modeler, Apache Airflow
• Governance: Data masking, metadata management, SOX compliance
• Soft Skills: Communication, problem-solving, stakeholder engagement
• Experience in Data Eng > 7 years