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Mid-level generalist data/backend role, metro location, and broad skills make competition high.
Core data engineering skills are transferable across industries, though media domain experience is a minor preference.
Explicit 4–6 years and multiple mandatory data/backend technologies make shortlisting strict.
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Design, develop, and maintain large-scale, high-performance data pipelines and backend systems for multimedia metadata solutions.
Ensure scalability, reliability, and performance of data platforms handling fast refresh cycles and complex datasets.
Collaborate cross-functionally to translate business needs into technical solutions and mentor junior engineers in best practices.
4 to 6 years of professional experience in Backend and Data Engineering with large-scale data and real-time event processing.
Proficiency in Python, Java, or Scala and experience with distributed data systems like Spark or Flink.
Experience designing and maintaining scalable RESTful APIs and backend frameworks, plus knowledge of cloud platforms (AWS, Azure, or GCP).
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experienced in large-scale data architecture involving distributed storage systems (HDFS, S3) and Lakehouse architectures (Delta Lake, Paimon).
Skilled in high throughput, low latency, and cost-efficient system design with strong data governance and observability focus.
Capable of working in agile environments with CI/CD practices and collaborating effectively across technical and non-technical teams.