Overview
We are seeking a Big Data Engineer with strong experience in banking and Anti-Money Laundering (AML) systems to design and build scalable data solutions on modern lakehouse platforms. The role focuses on developing robust data pipelines, enabling real-time and batch processing, and supporting AML analytics and compliance reporting. The ideal candidate will have hands-on experience with lakehouse architecture and a solid understanding of financial data and regulatory requirements.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines for AML and financial data processing.
- Build and optimize data solutions on lakehouse architecture/platforms (e.g., Delta Lake, Databricks, Iceberg).
- Ingest, transform, and process large volumes of structured and unstructured banking data.
- Support AML use cases including transaction monitoring, risk scoring, and regulatory reporting.
- Collaborate with data analysts, data scientists, and compliance teams to deliver data-driven AML insights.
- Ensure data quality, governance, and integrity across all data pipelines.
- Optimize data workflows for performance, scalability, and cost-efficiency.
- Integrate data from multiple banking systems including core banking, payment systems, and external sources.
- Implement data security and compliance controls aligned with regulatory standards.
- Troubleshoot data issues and provide ongoing support for production systems.
Job Qualifications and Requirements
- Proven experience as a Big Data Engineer within banking or financial services.
- Strong understanding of AML processes, financial crime data, and compliance requirements.
- Hands-on experience with lakehouse architecture/platforms (must-have).
- Experience with big data technologies such as Spark, Hadoop, Kafka, or similar.
- Proficiency in Python, Scala, or Java for data engineering tasks.
- Experience with ETL/ELT pipelines and data integration frameworks.
- Strong knowledge of data modeling, data warehousing, and distributed systems.
- Experience working with cloud platforms (AWS, Azure, or GCP) is preferred.
- Strong analytical, problem-solving, and communication skills.
