Data Engineer

Lorven Technologies Inc.; Chennai District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Lorven Technologies Inc. is seeking a Full Stack Data Engineer based in Chennai, India, with over 5 years of experience working in data engineering. The candidate will design and optimize scalable data solutions using Microsoft Fabric, manage data pipelines, and collaborate across various teams.

The role demands strong SQL and Python skills, and offers opportunities to innovate using AI-assisted development. Join us to impact business outcomes through data and analytics.

Qualifications

• 5+ years of experience in Data Engineering.
• Hands-on experience with Microsoft Fabric preferred.
• Strong Azure Data Engineering background with willingness to work across full-stack and AI-enabled engineering workflows.

Responsibilities

• Design and maintain scalable Lakehouse solutions using Medallion Architecture principles.
• Develop and manage pipelines using Fabric Data Factory, Notebooks, and Spark workloads.
• Implement orchestration, scheduling, monitoring, and recovery mechanisms for enterprise data pipelines.
• Collaborate with Data Architects, Analysts, BI Developers, Product Teams, and Business Stakeholders.

Skills

Microsoft Fabric (Fabric Data Factory, OneLake, Lakehouse, Spark Notebooks)

Strong SQL skills (joins, aggregations, optimization)

Python / PySpark for data transformation

Exposure to REST APIs and backend integrations

Basic to intermediate ReactJS knowledge

Understanding of AI-assisted development workflows

Tools

Azure Functions

Logic Apps

Power BI semantic models

Job description

A hands‑on Full Stack Data Engineer responsible for designing, building, and optimizing scalable Microsoft Fabric‑based data and analytics solutions. The role requires expertise across data engineering, cloud integration, AI‑assisted development, and lightweight application integration, with a focus on rapid delivery, reliability, scalability, and business impact.

Experience 5+ Years

Overview

We are seeking a highly motivated and hands‑on Full Stack Data Engineer with strong experience in Microsoft Fabric and modern Azure‑based data platforms. The ideal candidate should be capable of working across the full stack of data engineering — from ingestion and transformation to Gold‑layer curation, analytics enablement, API integration, and AI‑assisted application workflows.

This role requires engineers who can work independently, leverage AI‑assisted development for rapid delivery, and collaborate across data, cloud, and lightweight application layers. Exposure to MCP (Model Context Protocol), ReactJS integration, and modern AI‑enabled engineering practices is highly preferred.

1. Fabric Ecosystem & Full Stack Data Engineering

• Work with organizational OneLake structures, creating and managing shortcuts for efficient enterprise‑scale data access
• Design and maintain scalable Lakehouse solutions using Medallion Architecture principles (Bronze, Silver, Gold)
• Build and optimize Delta Lake tables for reporting, analytics, and AI workloads
• Develop and manage pipelines using Fabric Data Factory, Notebooks, and Spark workloads
• Build ingestion and transformation workflows supporting structured and semi‑structured data
• Implement orchestration, scheduling, monitoring, and recovery mechanisms for enterprise data pipelines
• Implement dimensional models (Star Schema/Snowflake Schema) to support BI, reporting, and semantic layer requirements
• Build curated Gold‑layer datasets for downstream analytics and AI consumption
• Support integration with Power BI semantic models and reporting platforms
• Develop batch and incremental pipelines from ADLS Gen2, APIs, Azure SQL, Blob Storage, and external systems
• Support ETL/ELT orchestration using Fabric Pipelines and Azure Data Factory
• Integrate Fabric‑based data platforms with APIs, AI services, and enterprise applications
• Support MCP (Model Context Protocol) integration and AI‑enabled workflows where required
• Collaborate on AI‑assisted development and rapid prototyping initiatives
• Work with lightweight ReactJS‑based applications and frontend integrations
• Support development of internal dashboards, data‑driven applications, and AI‑enabled user experiences
• Support automation using Azure Functions, Logic Apps, and event‑driven workflows
• Work with Git, CI/CD pipelines, Azure DevOps, and deployment automation processes

3. Data Processing, Optimization & AI‑Assisted Development

• Develop and optimize PySpark notebooks for transformation, cleansing, and enrichment
• Build efficient SQL queries, views, and stored procedures in Fabric Warehouse / Azure SQL
• Implement optimization techniques including partitioning, caching, and query tuning
• Monitor pipeline performance, troubleshoot failures, and improve system reliability
• Implement logging, alerting, and operational best practices
• Utilize AI‑assisted development tools such as GitHub Copilot and modern AI coding assistants
• Rapidly prototype and deliver scalable engineering solutions with minimal guidance

4. Governance, Security & Collaboration

• Implement RBAC and secure data access across Fabric workspaces and Azure environments
• Apply data quality validations and governance best practices
• Support metadata management and lineage using Microsoft Purview
• Collaborate with Data Architects, Analysts, BI Developers, Product Teams, and Business Stakeholders
• Translate business requirements into scalable data and application solutions
• Participate in Agile delivery processes, code reviews, and pull request workflows

Must‑Have Skills

• Microsoft Fabric (Fabric Data Factory, OneLake, Lakehouse, Spark Notebooks)
• Strong SQL skills (joins, aggregations, optimization)
• Python / PySpark for data transformation
• Exposure to REST APIs and backend integrations
• Basic to intermediate ReactJS knowledge
• Understanding of AI‑assisted development workflows

Good to Have

• Azure Functions / Logic Apps
• Power BI semantic models

Experience

• 5+ years of experience in Data Engineering
• Hands‑on experience with Microsoft Fabric preferred
• Strong Azure Data Engineering background with willingness to work across full‑stack and AI‑enabled engineering workflows
• Strong problem‑solving and debugging skills
• Ability to work independently with minimal guidance
• Strong ownership mindset and delivery focus
• Good understanding of ETL/ELT and cloud‑native data platforms
• Ability to collaborate across engineering, analytics, and application teams
• Adaptability in fast‑paced AI‑enabled development environments

Certifications (Preferred)

• DP-700: Fabric Data Engineer Associate