Risk Data Engineer Senior

Join EY's Technology team in Pune, India, and contribute to building innovative digital solutions at scale for the next generation of Financial and Non-Financial services globally. This is a senior, hands-on technical delivery role for a Risk Data Engineer/Lead with 3-6 years of experience. You will leverage groundbreaking cloud and big data technologies, focusing on data engineering, cloud infrastructure, platform engineering, and production support.

The ideal candidate possesses strong technical skills, a passion for learning, and a keen interest in Financial Crime, Financial Risk, and Compliance technology transformation. You should be adept at working collaboratively in a fast-paced environment and quickly mastering new tools and techniques.

Key Responsibilities:

• Gain a deep understanding of the data science lifecycle, including data exploration, preprocessing, modeling, validation, and deployment.
• Design, build, and maintain tree-based predictive models (decision trees, random forests, gradient-boosted trees) with a strong grasp of their underlying algorithms.
• Ingest and provision raw datasets, enriched tables, and curated data assets for various use cases.
• Evaluate and implement modern data engineering technologies, frameworks, and tools to drive innovation and enhance data processing capabilities.

Core/Must-Have Skills:

• Significant experience in data analysis using Python, SQL, and Spark, including scripting for data transformation, integration, and automation.
• 3-6 years of experience with cloud ML platforms (AWS) or similar.
• Proficiency in designing, building, and maintaining tree-based predictive models.
• Strong experience with statistical analytical techniques, data mining, and predictive modeling.
• Experience conducting A/B testing and other model validation methods.
• Experience with optimization modeling, machine learning, forecasting, and/or natural language processing.
• Hands-on experience with AWS services including Amazon S3 for data storage and lifecycle management, and integration with other AWS services.
• Experience maintaining, optimizing, and scaling AWS Redshift clusters for efficient data storage, retrieval, and query performance.
• Experience implementing CI/CD pipelines in AWS.
• At least 4 years of experience in Database Design and Dimension modeling using SQL.
• Advanced SQL knowledge, with experience working with relational and NoSQL databases (e.g., SQL Server, Neo4J).
• Strong analytical and critical thinking skills for resolving issues in data pipelines and systems.
• Excellent communication skills for effective team collaboration and stakeholder presentations.
• Experience collaborating with cross-functional teams.
• Familiarity with OLAP, OLTP databases, and data structuring/modeling.

Good to Have:

• Domain knowledge in financial fraud to enhance predictive modeling and anomaly detection.
• Knowledge of AWS IAM for secure data resource access.
• Familiarity with DevOps practices and automation tools (e.g., Terraform, CloudFormation).
• Experience with data visualization tools (e.g., Quick Sight) or integrating Redshift data with BI tools (e.g., Tableau, PowerBI).
• AWS certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect).