Job Description

Responsibilities

• Develop, implement and support OFSAA FCCM suite of products.
• Perform ongoing maintenance and support with Oracle Enterprise Data Quality tool (EDQ).
• Configure changes for Customer Screening using EDQ.
• Configure and load new watchlists in EDQ.
• Create new processes/jobs in EDQ for Watchlist Filtering and Customer Screening.
• Perform Customer Screening model validation and recalibration of the system.
• Identify and configure new alert types and new workflows using PMF.
• Analyze source system data and map data attributes to target data models.
• Configure Jurisdictions, Case Types, Threshold Sets, and Exception actions.

Requirements

• 3 to 6 years of experience implementing/supporting OFSAA FCCM solutions.
• Strong subject matter expertise in AML, KYC, Customer Screening, and Enterprise Case Management.
• Hands-on experience with Oracle EDQ — configuration, watchlist management, process creation.
• Experience with FCCM Workflow and scenario development.
• Experience with CRR and CTR.
• Good knowledge of FCCM data models (CASA and FCDM).
• Experience across OFSAA solutions — Transaction Monitoring and Client Risk Rating.
• Strong knowledge of SQL, PL/SQL, and Unix.
• Understanding of Regulatory Compliance domain including AML Transaction Monitoring.
• Experience in Machine learning and Data Analytics is added advantage.
• Strong exposure and understanding on the AI and Agentic AI technologies.

##LI-DNI

Qualifications
Key Responsibilities:
Design, build, and maintain robust ETL/ELT data pipelines using Apache
Spark on Databricks.
Implement data Lakehouse architecture using Delta Lake for cost-effective
data storage and analytics.
Use Databricks Workflows for orchestrating batch and streaming pipelines.
Develop and maintain CI/CD pipelines for data applications using tools such
as Azure DevOps, GitHub Actions or Databricks Repos.
Monitor pipeline performance and troubleshoot data issues in real-time and
batch environments.
Document solutions, workflows, and technical standards.
Required Skills:
Experience in data engineering with a strong focus on Databricks and
Apache Spark.
Proficiency in PySpark, SQL, and Python.
Experience with Delta Lake, Databricks SQL, and Unity Catalog.
Hands-on experience with cloud platforms
Familiarity with data lakehouse architecture, data warehousing and
streaming data
Strong understanding of ETL best practices, data partitioning, and
performance tuning.
Experience with CI/CD for data pipelines.
Excellent problem-solving and communication skills.