Related skills
etl data warehouse langchain llamaindex autogen📋 Description
- Lead and mentor Data Engineers to build scalable data pipelines for batch and real-time workloads.
- Champion Agentic AI adoption: text-to-SQL, data quality remediation, pipelines.
- Define guardrails and evaluation frameworks for safely deploying AI agents in the data lifecycle.
- Architect and implement robust Data Warehouse and Data Mart solutions, data modeling and ETL.
- Design analytics-ready Data Marts using star and snowflake schemas.
- Define and implement cloud-based data infrastructure with modern architectures.
- Drive technical excellence and delivery on mission-critical projects in a fast-growing environment.
- Partner with cross-functional teams to translate business requirements into data solutions.
🎯 Requirements
- At least 8+ years in Data Engineering, Data Warehousing, or Data Mart roles.
- Practical experience building offline and real-time Data Warehouses.
- Familiarity with Data Warehouse modelling theory and design; real-world use cases.
- Familiarity with Agentic AI frameworks (LangChain, LlamaIndex, AutoGen) for production in data.
- Experience building AI-powered data tools: NL query interfaces, anomaly remediation agents, observability.
- Hands-on with Agentic AI in data engineering: text-to-SQL, LLM remediation, metadata lineage.
🎁 Benefits
- Competitive total compensation package.
- L&D programs and Education subsidy for growth and development.
- Team building programs and company events.
- Wellness and meal allowances.
- Comprehensive healthcare schemes for employees and dependants.
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