Role: Data Engineer & AI Tech Lead

Experience:
6+ Years Work

Location:
Remote Shift: General Shift (IST) Contract Duration: 6 Months (Possible Extension) We are looking for an experienced and hands-on Data Engineer & AI Tech Lead to join an exciting project with a strategic energy-sector client based in Singapore. The ideal candidate should have strong expertise in Azure Databricks, Microsoft Fabric, Python, PySpark, SQL, Data Engineering, and AI/ML, along with the ability to design scalable solutions, lead technical initiatives, and collaborate directly with client stakeholders.

Key Responsibilities
• Design, develop, and maintain scalable enterprise data platforms using Azure Databricks and Microsoft Fabric.
• Build and optimize ETL/ELT pipelines for ingestion, transformation, and integration of data from multiple sources.
• Implement data lakehouse architectures, data warehousing solutions, and effective data models.
• Develop high-performance data processing solutions using Python, PySpark, and SQL.
• Establish data quality checks, monitoring, validation, and error-handling mechanisms.
• Optimize pipeline performance, query execution, resource utilization, and cloud costs.
• Implement data governance, security controls, and enterprise data management best practices.




• Design and implement AI-powered applications, predictive models, and intelligent automation solutions.
• Work with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks.
• Integrate AI/ML capabilities into enterprise data platforms and business applications.
• Develop proof of concepts and transform successful prototypes into production-ready solutions.
• Evaluate AI solutions for accuracy, performance, scalability, security, and business impact. Required Technical

Skills:
• Cloud Platforms: Microsoft Azure, Azure Databricks, Microsoft Fabric
• Programming: Python, PySpark, SQL
• Data Engineering: ETL/ELT, Data Pipelines, Data Integration, Data Lakehouse, Data Warehousing, Data Modelling
• AI/ML: Generative AI, LLMs, RAG, AI-powered Applications, Predictive Analytics
• Backend Development: REST APIs, Python-based Services, Software Integrations
• DevOps: Git, CI/CD, Automated Testing, Deployment Automation
• Architecture: Cloud-Native Solutions, Distributed Data Processing, Security, Data Governance
• Leadership: Technical Ownership, Solution Design, Stakeholder Management, Mentoring

📌 Data Engineer (India)
🏢 Gravity Infosolutions
📍 India