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Tier-1 brand, hybrid work, generic Software Engineer title, metro location, and broad skillset increase competition.
Data engineering skills (Python, SQL, ETL, cloud) are broadly transferable across industries.
Moderate technical must-haves (Python, SQL, cloud, Spark preferred) but no explicit years requirement.
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Design, develop, test, and maintain scalable applications and data solutions leveraging Python, SQL, cloud-native tools, and ETL workflows.
Implement and optimize CI/CD pipelines including automated testing and deployment to ensure high-quality delivery.
Monitor application performance, troubleshoot production issues, and contribute to architecture and code quality improvements across cross-functional teams.
Strong proficiency in Python and SQL; experience with Spark/Scala is advantageous.
Familiarity with cloud platforms such as AWS or Azure, containerization (Docker), and orchestration (Kubernetes).
Experience with software development lifecycle (SDLC), version control (Git), and unit/integration testing.
Work Experience Required: Not explicitly mentioned in the JD.
Technically skilled engineer with experience across cloud platforms and modern engineering practices including CI/CD pipelines.
Comfortable working in hybrid office/remote environments collaborating with product, data, and platform engineering teams.
Capable of owning end-to-end application lifecycle from development to monitoring and troubleshooting in production environments.