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Medium — known global consultancy and sought-after data skills but senior banking specialization reduces applicant density.
High — requires banking AML experience and niche Actimize and enterprise data engineering expertise.
High — explicit 8–10 years and mandatory specialized banking and data engineering technology requirements.
Develop, configure, and maintain NICE Actimize DART investigative components and queries to support AML, Fraud, Compliance, and Investigations teams.
Architect and deploy high-throughput batch and real-time streaming data pipelines for processing complex financial transactions, ensuring data governance and security compliance.
Lead legacy-to-cloud migration and optimize performance of SQL queries and distributed computing jobs; mentor mid-level data engineers and collaborate with architects and compliance teams.
8 to 10 years of experience in data engineering, software development, or enterprise data architecture in banking (retail, commercial, or investment).
Expert proficiency in Python, Scala, or Java and advanced ANSI SQL skills.
Hands-on experience with Apache Spark, PySpark, Hadoop, and real-time streaming platforms like Apache Kafka or AWS Kinesis.
Deep expertise in cloud data platforms (Snowflake, AWS Redshift, Google BigQuery, Databricks) and cloud infrastructure (AWS, Azure, or GCP).
Experienced in financial services data engineering with a focus on AML, Fraud, and Compliance data use cases.
Skilled in building and optimizing scalable data architectures in cloud environments with real-time and batch processing capabilities.
Capable of leading technical migration projects, performance tuning, and mentoring engineering teams within regulated banking contexts.