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Tier-1 brand, metro location, and popular data-engineer title increase applicant competition.
Data engineering skills are transferable but preference for financial services experience increases domain specificity.
Moderate technical requirements (GCP, Spark, Beam) but no explicit years requirement.
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Design, develop, and deliver significant engineering components and new application features focused on data workflows and software deployment.
Develop and deploy source code including infrastructure and application configurations involving Java, Python, Apache Beam/Spark, workflow orchestrators, and cloud services (GCP).
Support L3 debugging, code reviews, unit and integration testing, release deployments, and collaborate across the SDLC to ensure quality and maintainability.
Bachelor of Science degree in Computer Science or Software Engineering (or equivalent) with a minor in Finance, Mathematics or Engineering.
Proficient in Java/Scala, Apache Spark/Apache Beam, GCP Data Engineering services, workflow orchestrators like Airflow, and automation with Python/Terraform.
Strong analytical and communication skills with fluent English (written and verbal).
Work Experience Required: Not explicitly mentioned in the JD.
Experience working in financial services with relevant domain knowledge in core processes and SDLC tools (e.g., HP ALM, Jira, ServiceNow, Agile).
Capable of managing software integration, quality assurance including test strategy, architectural implementation, and release management in a matrixed virtual team environment.
Exposure to cloud data engineering, workflow orchestration, and automation technologies with an ability to support technical continuous improvements and knowledge transfer.