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Tier-1 brand, metro location, mid-level generalist Data Engineer with broad skills and cloud requirements.
Explicit financial-services experience requirement reduces cross-industry transferability.
Strong big-data tech requirements and financial-services experience make shortlisting highly selective.
Design, develop, and deliver key engineering components for big data applications including Hadoop and Spark infrastructure, ensuring solutions are fit for purpose and maintainable.
Lead Level 3 support for technical infrastructure components, troubleshooting production incidents and supporting Level 2 teams.
Drive continuous improvement initiatives on big data applications, contribute to code reviews, testing, release deployments, and maintain development and deployment documentation.
Bachelor's degree in Computer Science, Software Engineering, or equivalent with minor in Finance, Mathematics, or Engineering.
Strong proficiency in Java/Scala, Spark, Hadoop Hive, and workflow orchestrators like Airflow, Control-M, Composer; scripting skills in Python/Bash/Shell.
Experience with cloud services preferably Google Cloud Platform (GCP) and knowledge of IT delivery and architecture including Data Modelling and analysis.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working in financial services domain with exposure to relevant business areas and SDLC methodologies including Agile and tools such as Jira, HP ALM, and Service Now.
Capable of operating in virtual teams and matrixed organizations, balancing IT delivery and business needs for scalability, reliability, and performance.
Proven ability to leverage AI tools responsibly for productivity improvements and problem-solving in software engineering contexts.