Description

Job Description

Must Have Technical/Functional Skills:

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives.

Qualifications & Skills:

• 10+ years of experience in Data Engineering, Data Warehousing, Analytics, or Data Management.
• 3+ years of experience as a Data Architect designing enterprise-scale data solutions.
• Strong BFSI, Payments, FinTech, or Fraud/Risk domain experience, including fraud detection, AML, KYC, transaction monitoring, and risk analytics.
• Expertise in Data Architecture, Data Modeling, Data Lake/Lakehouse, Data Warehouse, ETL/ELT, Data Governance, and Metadata Management.
• Hands-on experience with SQL, Python, Spark/PySpark, Databricks, Kafka, Airflow, Snowflake, and modern cloud platforms.
• Knowledge of real-time streaming, event-driven architectures, MDM, Data Mesh, and ML/AI-enabled data platforms.
• Strong leadership, stakeholder management, communication, and solution design skills.

Roles & Responsibilities:

• Define and implement enterprise data architecture, data models, governance standards, and technology roadmaps for fraud and risk analytics platforms.
• Design and oversee scalable batch and real-time data pipelines, data lakes/lakehouses, data warehouses, and cloud-based data solutions.
• Partner with Fraud, Risk, Compliance, and Business teams to deliver solutions supporting fraud detection, transaction monitoring, AML, behavioral analytics, and regulatory reporting.
• Ensure data quality, security, lineage, compliance, performance optimization, and adherence to architecture best practices.
• Lead architecture reviews, mentor engineering teams, and collaborate with stakeholders to drive data modernization initiatives

Key Skills

Education

Any Graduate