The Lead Data Engineer will design, build, and operationalize scalable data solutions to support enterprise analytics and AI/ML initiatives. This role requires expert-level proficiency in Databricks, Azure Fabric, PySpark, SQL, and the Azure ecosystem, with deep experience across data warehouses, data lakes, and real-time integration. The Lead Data Engineer will architect end-to-end pipelines using industry-standard tools, drive automation, and move solutions effectively into production. The incumbent will ensure compliance with data governance requirements (including GxP and HIPAA/GDPR) while building reusable, integrated pipelines and analytical models that promote self-service analytics. This role provides technical leadership across the team, mentors junior engineers, and partners with business stakeholders to align data engineering with organizational objectives.

About the Role
. Data Architecture & Engineering
Architect, design, and implement end-to-end data solutions using Azure Databricks, PySpark, Azure Data Factory, and Azure SQL.
Design, build,



and maintain data pipelines from data sources through integration to consumption for specific use cases.
Implement robust data modeling standards across bronze, silver, and gold layers in the data lake.
Develop data models (conceptual, logical, and/or physical) as required.
Optimize Spark and SQL workloads for performance, scalability, and cost efficiency.
Manage metadata using data preparation, integration, and AI-enabled tools and techniques.

. Data Integration & Automation
Drive automation in data integration; recommend and lead implementation of techniques to automate repeatable data preparation and integration tasks.
Build API-based integrations (REST/JSON) and real-time ingestion frameworks.
Automate data workflows using Azure DevOps pipelines and Git-based CI/CD practices.
Implement parameterized, reusable pipeline templates for ingestion and transformation.
Develop automated unit, r

📌 Senior Data Engineer Bengaluru
🏢 Alimentiv
📍 Bengaluru