Key responsibilities

- Design, develop, test, and maintain Python applications, services, utilities, and data-processing workflows.
- Write complex, optimized SQL for data extraction, transformation, reconciliation, profiling, and investigation use cases.
- Work with large financial datasets, including customer, account, transaction, alert, case, and screening data.
- Translate Financial Crime Compliance requirements into technical designs, data rules, scenarios, and reusable components.
- Support KYC and AML workflows such as customer onboarding, customer risk rating, customer due diligence, enhanced due diligence, and periodic review.
- Contribute to Transaction Monitoring, Sanctions, and Fraud solutions, including rule implementation, threshold logic, alert generation, data validation, and issue analysis.
- Develop APIs, batch jobs, automation scripts, and integration components using Python.
- Perform unit testing, code reviews, debugging, root-cause analysis, and production support.
- Collaborate with compliance SMEs, business analysts, data engineers, QA teams, and client stakeholders in Agile delivery teams.
- Follow secure coding, version-control, documentation, and deployment practices. Primary skills must have
- Python: Strong hands-on programming experience, including data structures, functions, object-oriented programming, exception handling, modules, logging, testing, and performance-conscious coding.
- Advanced SQL: Robust command of complex joins, subqueries, common table expressions, window functions, aggregations, query optimization,



stored procedures, and data reconciliation.
- Databases: Practical experience with at least one relational database such as PostgreSQL, Oracle, Microsoft SQL Server, or MySQL.
- Data engineering: Experience processing structured data using Python libraries such as pandas and integrating with databases, files, or APIs.
- APIs and services: Working knowledge of REST APIs and Python frameworks such as FastAPI, Flask, or Django.
- Engineering practices: Git, unit testing, code review, debugging, documentation, and CI/CD fundamentals.
- Cloud: Mandatory hands-on experience with at least one cloud platform: Microsoft Azure, AWS, or GCP. Candidates should have practical experience developing, deploying, or supporting data-driven applications or services in a cloud environment. Good to have
- Experience with PySpark or distributed data processing.
- Familiarity with orchestration or ETL tools such as Airflow, Azure Data Factory, or equivalent.
- Experience with data visualization or reporting tools such as Power BI or Tableau.
- Understanding of model or rule performance measures, threshold tuning, false-positive reduction, and data lineage.




- Exposure to Agile delivery tools and practices, including Jira or Azure DevOps. Financial Crime domain knowledge
- KYC / CDD / EDD: Customer onboarding, identity and document checks, customer risk rating, beneficial ownership, periodic review, and remediation.
- AML: Financial crime risk indicators, typologies, alert and case workflows, investigations, escalation, and regulatory reporting concepts.
- Transaction Monitoring (TM): Scenario or rule logic, thresholds, segmentation, alert generation, tuning support, back-testing, and data-quality controls.
- Sanctions: Customer and payment screening, watchlist concepts, potential-match handling, disposition workflows, and screening data quality.
- Fraud: Fraud indicators, rules or models, event and transaction analysis, alert triage, investigations, and case outcomes. Experience and education
-

Experience:
Strictly 2–4 years of relevant professional experience in software engineering, data engineering, analytics engineering, or technology delivery.
- Eligibility: Freshers and candidates with less than 2 years of relevant experience will not be considered.
- Cloud

experience:
Hands-on experience with Microsoft Azure, AWS, or GCP is mandatory.
- Domain

experience:
Relevant delivery experience in KYC, AML, Transaction Monitoring, Sanctions, or Fraud is good to have.
-

Education:
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.

📌 Python - SQL developer (Delhi)
🏢 EY
📍 Delhi