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Strong employer brand, popular data role, mid-level experience band, and Bangalore metro increase applicant competition.
Data engineering skills transfer well across industries; AI/knowledge-graph experience is moderately transferable.
Wide 0–7 years range but specific data engineering and RAG skills create moderate filtering.
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Build and maintain scalable backend data pipelines and ETL/ELT workflows for AI-powered enterprise applications.
Develop and support retrieval augmented generation (RAG) pipelines, vector indexing, knowledge graph assets, and semantic data enrichment under senior guidance.
Ensure data quality, validation, reconciliation, and optimize pipeline performance across batch and near-real-time workloads.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
0–7 years of experience in data engineering, software engineering, or related technical role.
Proficiency in Python and SQL and/or Java.
Basic understanding of ETL/ELT pipelines, data transformation, data integration; exposure to big data tools like Spark or Databricks is preferred.
Experience working with AI-enabled data systems, including knowledge graphs and semantic search concepts.
Comfortable in technical environments involving orchestration tools such as Airflow and big data processing platforms.
Able to collaborate in engineering discussions and code reviews while learning from senior engineers in a structured delivery setting.