Seasoned Data Engineer and Subject Matter Expert (SME) in Anti-Money Laundering (AML), with a proven track record in optimizing data workflows and implementing comprehensive data solutions. Highly proficient in designing and managing complex data pipelines, ensuring data quality, and employing advanced analytical techniques to address intricate challenges within the Financial Crime and Compliance domain.- 10 years of industry experience with a demonstrated ability to leverage advanced data engineering techniques and scientific methods to solve real-world problems in the Risk and Compliance domain.- Expert in utilizing Python and libraries like Pandas and NumPy for efficient data manipulation and analysis.- Skilled in SQL, PL/SQL, and NoSQL databases such as MongoDB and Cassandra for robust data management and querying.- Hands-on experience with AWS services including Lambda, EC2, S3, RDS, CloudWatch, SES, and SMS, supporting scalable data solutions.- Proficient in Apache Spark and PySpark for large-scale data processing and transformation, with hands-on experience in leveraging Databricks for efficient and collaborative data engineering workflows.- Proven ability to analyze diverse data sets, from user profiles to transaction histories, and identify emerging risk patterns through data mining techniques.- Extensive experience in ETL processes for financial data, ensuring accurate data integration and transformation to support business intelligence.https://www.credly.com/badges/c3a3b108-df72-4bc6-a77b-c9f5256b9e7d/public_urlroficient