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Tier-1 brand, metro location, and a popular data-engineer title create moderate applicant competition.
Core big-data and cloud engineering skills are transferable, though finance/compliance experience is a beneficial differentiator.
Explicit 10+ years and required Spark/Scala/Python plus cloud/Databricks skills create strict screening filters.
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Design, build, test, and maintain scalable data architectures and pipelines aligned with business and compliance requirements.
Ensure data quality, governance, and implement data security measures within large-scale processing systems.
Collaborate with data scientists and analysts to support data accessibility and efficient processing for business and compliance use cases.
Bachelor’s degree in computer science or engineering.
Minimum 10+ years of hands-on experience in data-focused application development (ETL, data engineering).
3+ years hands-on experience with Scala and Python programming.
2+ years experience with public cloud technologies such as AWS and Databricks required.
Experienced in building and optimizing Spark jobs for performance and cost efficiency within cloud environments.
Prior experience in finance, custody services, or compliance domains including data privacy and AML is a plus.
Familiarity with CI/CD pipelines, orchestration tools, and production pipeline monitoring to troubleshoot data issues effectively.