Data Engineer (Level 23) AML Program - F2F interview Mandatory

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)