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Niche Teradata/Databricks specialization and seniority reduce competition despite Bangalore location.
Specialized enterprise data warehouse and Databricks skills limit cross-industry portability somewhat.
Multiple mandatory technologies and domain-specific deliverables enforce strict technical screening.
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Ingest, validate, and integrate 18+ months of Teradata DBQL logs and metadata from scheduling and orchestration tools to enable comprehensive data usage analysis.
Build end-to-end analysis pipelines in Databricks to identify unused datasets, read-only data, partition usage, and quantify resource consumption for cost reduction opportunities.
Develop AI/ML or LLM-assisted models to detect anomalies, classify data temperature tiers, and provide prioritized, actionable recommendations with risk and savings projections to stakeholders.
Experience working with Teradata DBQL logs and metadata integration from tools like Autosys and DataStage.
Proficiency in building data pipelines and analyses in Databricks environment.
Familiarity with applying AI/ML models or large language models for anomaly detection and data classification.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in end-to-end data engineering with a focus on database workload and resource usage analysis for cost optimization.
Skilled in integrating multiple metadata sources to augment data analysis and develop actionable business recommendations.
Proficient in applying AI/ML techniques or LLMs to automate data pattern detection and classification in large scale enterprise environments.