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Tier-1 employer, Bangalore location, and a common Data Engineer title increase applicant competition.
Core data engineering and ML pipeline skills transfer easily across industries.
Extensive technical and ML-specific requirements but no explicit years yields moderate strictness.
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Design and develop a centralized data platform integrating diverse data sources such as APIs, databases, files, and streaming systems.
Build and maintain scalable Python-based data pipelines, data models, and feature stores optimized for machine learning and AI use cases including LLM applications.
Implement and monitor end-to-end data and ML pipelines ensuring data quality, lineage tracking, and support for model lifecycle workflows including training, deployment, and continuous improvement.
Proficient in Python for data ingestion, transformation, and pipeline development.
Experience with data modeling, database schema design, and data lineage systems.
B.E / B.Tech degree required.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable data backbones supporting AI/ML pipelines including feature stores and LLM-related data workflows.
Skilled in designing reusable data orchestration frameworks and integrating end-to-end ML model lifecycle management.
Capable of collaborating with domain experts to translate business logic into data models optimized for AI data preparation and processing.