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

NTT DATA North America

On-siteNew York City, NYleadPosted 2h ago

Job description

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.