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Popular senior data engineering title, Bangalore location, and broad required skillset increase applicant competition.
Core data engineering skills are transferable, but supply-chain/EDI and no-code platform domain knowledge adds specificity.
Strong mandatory data engineering and backend stack requirements indicate strict technical shortlisting.
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Design and develop the data backbone for a no-code data platform handling ingestion, transformation, validation, monitoring, and operational workflows.
Build scalable backend services including APIs, execution engines, and orchestration using Python, TypeScript, Go, or similar languages with production standards.
Implement metadata-driven frameworks and platform observability features such as logs, audit trails, data lineage, SLA monitoring, and data quality to ensure reliability and scalability.
Proven experience in backend engineering with scalable APIs, workers, or orchestration layers using Python, TypeScript, Go, or comparable languages.
Strong data engineering fundamentals including ingestion, transformation, validation, orchestration, metadata, and data quality monitoring.
Hands-on experience with relational databases (PostgreSQL, MySQL) and NoSQL technologies (MongoDB, Redis, or similar).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building configuration-driven, metadata-focused data platforms enabling no-code/low-code user interactions.
Familiar with distributed processing frameworks (e.g., Apache Spark, Apache Flink) and workflow orchestration tools like Apache Airflow.
Able to collaborate cross-functionally with product managers, architects, frontend engineers, and QA to translate complex requirements into scalable platform capabilities.