Senior Software Engineer- Data Engineering

•  Proficiency in Python and PySpark/Spark 

• Experience building and maintaining production-grade data pipelines 

• Strong understanding of data modeling, schema design, and data integrity principles 

• Experience with Databricks, Delta Lake, and distributed data processing systems or something similar 

• Experience designing scalable, reusable, and maintainable software components 

• Strong knowledge of unit testing, integration testing, and data validation techniques 

• Experience implementing monitoring, alerting, and operational observability 

• Familiarity with CI/CD pipelines, code review practices, and deployment workflows 

• Understanding of secure coding practices, secrets management, and static analysis remediation 

• Strong debugging, troubleshooting, and root-cause analysis skills

• Deliver production-ready, maintainable, and scalable solutions with minimal supervision 

• Ensure correctness and integrity of data transformations and downstream processing 

• Perform comprehensive self-review and validation before requesting peer review 

• Reuse existing shared utilities and platform standards wherever applicable 

• Design solutions with long-term scalability, maintainability, and operational support in mind 

• Validate positive, negative, and edge-case scenarios through automated and manual testing 

• Ensure monitoring, alerting, and operational readiness are fully validated prior to deployment 

• Demonstrate end-to-end ownership, including deployment verification and operational follow-through 

• Maintain clean, modular, and well-structured code with minimal duplication 

• Proactively identify production risks and implement preventive safeguards 

• Address review feedback completely and thoughtfully before resubmission 

• Contribute to engineering best practices, standardization, and reusable platform patterns

What to Bring:

• Bachelor's degree in computer science, Engineering, or related field 

• 5-8 Years of experience in software engineering or data engineering 

• Hands-on experience with Python and Spark/PySpark 

• Experience working with Databricks or similar distributed data platforms 

• Experience building and supporting production-grade ETL/data ingestion pipelines 

• Strong understanding of data validation, schema management, and transformation logic 

• Experience implementing unit tests and integration tests for data applications 

• Experience with monitoring, logging, alerting, and operational support processes 

• Familiarity with Git workflows, code reviews, and CI/CD practices 

  • Strong understanding of software engineering fundamentals and clean code principles