DE-RCE-Data Engineer- Risk M-GDSN02

Job Details

Career Family: FinCrime Data Engineer

Role Type: Full Time

Job Overview

We are looking for a Data Engineer at EY GDS. You will work on designing and implementing scalable data pipelines and solutions using modern data platforms such as Databricks or Snowflake. You will collaborate with cross-functional teams to build, deploy, and manage data workflows that meet business needs and leverage best practices in data engineering and cloud technologies.

Your key responsibilities

• Data Pipeline Development: Design, develop, and optimize data pipelines for large-scale structured and unstructured datasets.
• Data Handling: Work with SQL for data extraction, transformation, and analysis.
• ETL Workflows: Develop and maintain ETL workflows using PySpark or equivalent technologies.
• Platform Implementation: Implement scalable solutions on Databricks or Snowflake environments.
• Collaboration: Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality data products.
• Data Quality and Compliance: Ensure data quality, reliability, and compliance with regulatory standards.
• Domain-Specific Solutions: Contribute to domain-specific solutions for AML, fraud detection, and risk analytics.

Skills and attributes for success

Required Skills

• 7+ years of experience in data engineering, working with ETL pipelines, SQL, and modern data platforms
• Domain Knowledge: Experience in any 1 or more of these areas: AML (Anti Money Laundering) Modelling OR, Sanctions screening OR, Fraud OR, Financial Crime OR, Trade Surveillance
• PySpark / Scala Expertise: Hands-on experience with PySpark for data processing and working knowledge of Scala.
• SAS Compliance Packages: Hands-on experience working with SAS Compliance Solutions (AML, FCC, KYC, or Fraud) for data ingestion, data model understanding, or rule execution workflows.
• Modern Data Platforms: Experience working on Databricks
• Snowflake
• SQL and ETL Development: Strong skills in SQL, data handling, and ETL pipeline development for structured and unstructured data.
• Performance Optimization: Experience with performance optimization and handling large-scale datasets.
• Collaboration: Strong teamwork and communication skills with the ability to work effectively with cross-functional teams.

Preferred Experience

• Agile Methodologies: Familiarity with Agile development practices and methodologies.
• Problem-Solving: Strong analytical skills with the ability to troubleshoot and resolve complex issues.
• Cloud Platforms: Experience in one of the cloud data platforms (AWS, Azure, GCP)
• CI/CD Practices: Experience with CI/CD practices for data engineering
• GenAI / AI Familiarity: Awareness or training in Generative AI or AI concepts, such as LLMs, prompt engineering, or AI-based data workflows.

Education

• Degree: Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience

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