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Tier-1 employer, metro location, and a common Data Engineer title increase candidate competition significantly.
Core data engineering skills are transferable, though investment banking and risk domain preference increases industry specificity moderately.
Extensive mandatory cloud, Kubernetes, Kafka, CI/CD and leadership requirements create strict technical and experience filters.
Lead design and development of scalable data pipelines and AWS infrastructure to support data-driven decision making.
Apply advanced analytics, machine learning, and visualization to extract insights from large datasets influencing business strategies and operational improvements.
Drive platform initiatives, set technical strategy, advise senior stakeholders, and manage risk and governance related to data engineering functions.
Proven experience with Python, C/C++, Kafka, Solace, microservices, API development, SQL databases, and DevOps technologies.
Strong expertise in AWS infrastructure design and management including CloudFormation/Terraform, multi-account strategies, VPC design, API Gateway, and hybrid cloud architecture.
Experience with container orchestration technologies such as Docker and Kubernetes including cluster management and CI/CD pipeline engineering with GitLab, SonarQube, and Veracode.
Work Experience Required: Not explicitly mentioned in the JD; Location requirement: Based in Pune.
Experienced in leading multi-disciplinary engineering teams or acting as a subject matter expert with strong technical leadership in data engineering and cloud infrastructure.
Capability to interact effectively with senior stakeholders (VP/Director level) and influence cross-functional strategy and decision-making.
Strong analytical and strategic thinking skills with ability to translate complex data insights into actionable business recommendations and drive continuous process improvement.