Description:
Role Overview:
Client is seeking hands-on Data Engineers to support Client's AML program, focused on data migration from existing pipelines and building scalable, production-ready data infrastructure.
This is an individual-contributor role requiring the ability to work independently within an established data engineering environment.
Responsibilities:
-Build and maintain data pipelines and orchestration workflows supporting transaction monitoring and case management systems
-Support data migration efforts, leveraging and modernizing existing pipeline architecture, including migration onto Snowflake
-Develop and optimize PySpark-based batch and ETL jobs for large-scale data processing
-Develop and optimize data workflows across cloud data platforms (AWS, Snowflake)
-Partner with AML stakeholders and data engineering leads to define technical requirements
-Document data engineering architecture, standards, and dependencies
Required Skills:
-Python — hands-on experience with both is required (hiring manager is looking for Python, not one or the other)
-SQL — strong hands-on experience required
-AWS — required, hands-on cloud data engineering experience
-PySpark — hands-on experience building and optimizing distributed data processing jobs (batch/ETL pipelines, large-scale transformations) required
-Proven experience building and supporting production data pipelines at scale
Preferred Skills:
-Snowflake — hands-on experience with Snowflake as a cloud data warehouse strongly preferred, including schema design, performance tuning, and integrating Snowflake with upstream pipelines
-Experience migrating or modernizing pipelines onto Snowflake and/or Databricks
-Prior Client experience (current or former contractor/employee)
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