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Well-known financial brand, Bangalore metro, mid-level generalist data-engineer role increases applicant competition.
Core data engineering skills transferable across industries; knowledge-graph/RAG adds moderate specialization.
Explicit 5–12 years requirement plus required Python/SQL and data engineering skills.
Build and maintain scalable backend data pipelines, ETL/ELT workflows, and structured knowledge assets to support enterprise AI applications.
Contribute to big data processing, data integration, retrieval pipelines, and knowledge graph foundations enabling GenAI use cases.
Perform data quality checks, pipeline optimization, and support AI data enablement tasks including RAG pipelines, vector indexing, and metadata enrichment.
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
5–12 years of experience in data engineering, software engineering, or related technical roles.
Working knowledge of Python and SQL and/or Java; basic understanding of ETL/ELT, data transformation, and integration.
Preferred exposure to big data tools like Spark or Databricks, data lakes/warehouses, and familiarity with orchestration tools like Airflow.
Experienced with scalable data pipeline development for AI/ML systems and knowledge graph foundations.
Technically skilled in Python, SQL/Java, and big data processing frameworks, capable of contributing under senior guidance.
Comfortable working with data modeling, semantic enrichment, RAG pipelines, vector databases, and data governance concepts in enterprise environments.