Data + AI Engineer

DataE2E Technologies; India; On-site; INR 3,000,000 - 6,500,000; Full time

Job summary

DataE2E Technologies in India is hiring senior data engineering professionals to design and develop scalable data pipelines using Databricks, Spark and SQL, built on cloud-native architectures. The role emphasizes medallion-style data products (bronze, silver, gold) and robust ELT/ETL frameworks for batch and streaming workloads.

You will contribute to agentic AI engineering initiatives, aligning AI-generated code and artifacts with enterprise standards, building AI-assisted workflows, and

Qualifications

• 8+ years in Data Engineering, Analytics Engineering or Data Platform development.
• Hands-on experience building agentic AI solutions.
• Experience implementing enterprise-scale data pipelines and data products.
• Demonstrated experience with software engineering best practices and DevOps methodologies.
• Experience with Git, pull-request review, automated testing and CI/CD pipelines for analytics or data assets.
• Experience with natural-language analytics, MCP or spec-driven development; familiarity with responsible AI frameworks and AI cost controls.

Skills

Data Engineering

Analytics Engineering

Data Platform development

Agentic AI solutions

Data pipelines

DevOps methodologies

Git & CI/CD

Natural-language analytics

MCP or spec-driven development

Responsible AI frameworks

Job description

• Design and develop scalable data pipelines using Databricks, Spark, SQL and cloud-native
• technologies
• Build and maintain bronze, silver and gold data products following medallion architecture principles
• Develop robust ELT/ETL frameworks supporting batch and streaming workloads
• Implement data modeling standards, optimization strategies and performance tuning practices
• Ensure engineering solutions meet enterprise standards for scalability, reliability and maintainability

Agentic AI engineering

• Use Speckit and enterprise knowledge repositories to give AI agents contextual grounding, so
• generated code, documentation, tests and engineering artifacts align with organizational standards and
• best practices
• Design knowledge-driven agent workflows that draw on documented business rules, data models, architecture patterns and engineering guidelines
• Build AI-assisted solutions for: Spark and SQL code generation, Data pipeline generation
• Data quality rule generation, Unit test generation, Code review and optimization, CI/CD and deployment automation
• Develop multi-agent workflows that orchestrate end-to-end engineering tasks
• Script against REST APIs and SDKs (Power BI/Fabric, Databricks, Jira or Azure DevOps), and use
• Tabular Editor for bulk model changes
• Build evaluation harnesses for AI agents and orchestrate workloads with tools such as Databricks Jobs or Airflow
• Create reusable prompt frameworks, agent instructions, templates and engineering accelerators
• Define guardrails and quality controls for AI-generated code and artifacts
• Implement human-in-the-loop review and governance mechanisms

Experience

• 8+ years in Data Engineering, Analytics Engineering or Data Platform development
• Hands-on experience building agentic AI solutions
• Experience implementing enterprise-scale data pipelines and data products
• Demonstrated experience with software engineering best practices and DevOps methodologies
• Experience with Git, pull-request review, automated testing and CI/CD pipelines for analytics or data assets
• Experience with natural-language analytics, MCP or spec-driven development; familiarity with responsible AI frameworks and AI cost controls