Job Details

- Career Family: FinCrime Data Engineer
- Role Type: Full Time

Job Summary

Data Engineer at EY GDS. You will work on designing and implementing scalable data pipelines and solutions using up-to-date 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.

Required Skills
- 4+ 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
- Sanctions screening
- Fraud
- Financial Crime
- 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
- Excellent communication and reasoning skills
- GenAI / AI Familiarity: Awareness or training in Generative AI or AI concepts, such as LLMs, prompt engineering, or AI-based data workflows.

Education
- Degree: Bachelors degree in Computer Science, Information Technology, or a related field, or equivalent practical experience

📌 DE-RCE-Risk Data Engineer Sr-G (Bengaluru)
🏢 EY
📍 Bengaluru