Data Lead / Data Engineer / Data Architect / Data & AI Engineering Lead

Summary:

We are seeking an experienced Senior Data Practitioner / Data Lead to lead enterprise data initiatives across data engineering, governance, provisioning, analytics, and AI/ML. The role will support Financial Crime, Fraud Analytics, AML, KYC, and Risk functions, partnering with business stakeholders.

Key Responsibilities:

• Lead end-to-end data engineering, data management, governance, and analytics initiatives.
• Design and maintain scalable batch and real-time data pipelines and enterprise data lake solutions.
• Develop data ingestion, transformation, enrichment, and provisioning frameworks using Python, SQL, Spark, and Hadoop.
• Support Fraud, AML, Financial Crime, Risk, and machine learning use cases.
• Partner with Data Science/AI teams on feature engineering, model training, inference, deployment, and MLOps.
• Utilize PyTorch for ML workflows, fraud analytics, anomaly detection, and AI-driven automation.
• Implement data governance, quality, metadata, lineage, security, and compliance frameworks.
• Build monitoring and automation solutions for data quality and platform performance.
• Collaborate with distributed business and technology teams and mentor junior engineers.

Basic Qualifications:

• 8+ years of experience in Data Engineering, Data Management, Data Architecture, or Data Governance.
• 5+ years of experience in Banking, Financial Services, Capital Markets, or Financial Institutions.
• Strong experience with Fraud Analytics, Financial Crime, AML, KYC, Risk, or Regulatory Reporting.
• Strong hands-on expertise in Python, SQL, PyTorch, Apache Spark, Hadoop, and data architecture.
• Experience building real-time/near-real-time data platforms, enterprise data lakes, and ML/AI data pipelines.
• Strong understanding of MLOps and machine learning lifecycle management.
• Experience with enterprise data governance, data quality, metadata, lineage, security, and compliance.
• Experience with Linux, Shell scripting, Agile, CI/CD, Git, and DevOps.
• Strong communication, analytical, stakeholder management, and leadership skills.