AI & Data Analytics Engineer

Role & responsibilities

GenAI & Agentic AI

• Identify and develop practical GenAI and Agentic AI use cases across business functions.
• Build AI assistants, RAG solutions, AI agents and Natural Language-to-SQL solutions.
• Integrate AI solutions with enterprise applications, databases, APIs and workflows.
• Develop POCs and convert successful AI solutions into production.

Automation

• Identify repetitive and manual business processes for automation.
• Develop intelligent automation using AI, Python, APIs, workflow/RPA tools and other suitable technologies.
• Measure automation impact through productivity improvement, effort reduction and process efficiency.

Data Governance

• Drive Master Data and Transaction Data Governance across SAP and Non-SAP systems.
• Develop data-quality rules, validation mechanisms and exception monitoring.
• Identify duplicates, inaccuracies and inconsistencies and support corrective actions.
• Develop dashboards to monitor data quality and governance KPIs.

Analytics & Dashboards

• Develop interactive management and business dashboards using Power BI, SAP Analytics Cloud or similar platforms.
• Develop predictive analytics and forecasting models for Sales, Finance, Supply Chain, Inventory and other business functions.
• Convert complex data into actionable insights for management decision-making.
• Automate MIS and recurring business reporting.

Business Collaboration

• Work with business stakeholders to understand requirements and identify opportunities for AI, automation and analytics.
• Translate business problems into scalable technology solutions.
• Collaborate with SAP, IT and business teams for implementation and adoption.

Preferred candidate profile

Graduation is must

2 to 5 years of experience required in GenAI, Automation & Data Governance.

Strong Python, SQL, Excel and Data Analytics skills.

Knowledge of databases such as Oracle, PostgreSQL, MySQL or equivalent.