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Tier-1 brand, mid-level generalist title, and metro location increase candidate competition.
Core data engineering skills transfer across industries, though commerce-domain familiarity is beneficial.
Explicit 5-8 year requirement plus mandatory Python, Spark, Databricks and production ETL experience.
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Build, maintain, and operate production-grade data pipelines and backend APIs that support commerce monetization services for streaming platforms.
Ensure data correctness, integrity, and operational readiness through comprehensive testing, monitoring, alerting, and validation of data transformations and downstream processing.
Own end-to-end deployment, maintenance, and operational support for scalable, reusable, and maintainable software components and data processing systems.
Bachelor's degree in Computer Science, Engineering, or related field.
5-8 years of experience in software or data engineering.
Proficiency with Python, SQL, PySpark/Spark, and experience with Databricks or similar distributed data platforms.
Experience building and supporting production-grade ETL/data ingestion pipelines with strong knowledge of data validation, schema management, testing, monitoring, and CI/CD workflows.
Experienced in designing scalable, reusable, and maintainable data engineering solutions with strong software engineering fundamentals and clean code practices.
Comfortable with end-to-end ownership including deployment verification and operational follow-through in a global tech environment.
Familiar with implementing monitoring, alerting, operational observability, and secure coding practices in complex distributed data systems.