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Mid-level generalist data/backend role, Bangalore metro, broad tech stack increases applicant competition.
Core distributed data and cloud skills transfer well, but media/metadata domain adds moderate bias.
Explicit 4–6 years plus mandatory distributed data, cloud, and backend tech makes filters strict.
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Design, develop, and maintain scalable, high-performance data pipelines and backend systems for large-scale metadata solutions in video, audio, automotive, and sports domains.
Architect and implement data platforms ensuring scalability, reliability, high throughput, low latency, and cost-efficiency, adhering to data governance standards (lineage, quality, traceability).
Collaborate cross-functionally to deliver new features, troubleshoot complex issues, and mentor junior engineers while adopting emerging technologies including GenAI and LLMs.
4 to 6 years of professional experience in Backend and Data Engineering with large-scale datasets and real-time event processing.
Advanced programming skills in Python, Java, or Scala; experience with distributed data systems like Spark or Flink; and experience building scalable RESTful APIs.
Proficiency with cloud platforms (AWS, Azure, GCP), distributed storage systems (HDFS, S3), lakehouse architectures, and database systems (NoSQL and relational).
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experienced engineer comfortable delivering at scale in a backend and data platform environment, focused on performance, scalability, and robustness.
Ability to translate complex business requirements into technical solutions while maintaining data governance and SLA compliance.
Skilled collaborator and mentor who can operate in agile, fast-paced settings and leverage emerging AI tools to enhance product and engineering outcomes.