Role: Lead Data Engineer

Experience: 8 to 12 Years

Location: Chennai(Work from Office)

Full time - Permanent Role

Responsibilities:

- Design and build scalable, reliable data pipelines and ETL/ELT workflows across batch and near-real-time processing scenarios
- Develop and maintain data models across relational (SQL Server) and NoSQL (MongoDB, Atlas) systems to support analytical and operational use cases
- Build and manage data solutions on Microsoft Fabric — including Lakehouses, Warehouses, Dataflows, and Pipelines — to deliver a unified analytics platform
- Drive AI-enabled development practices within the team — leveraging AI coding assistants, LLM-based tools, and intelligent automation to accelerate pipeline development, improve code quality, and reduce manual effort
- Lead, mentor, and grow a team of data engineers; conduct code reviews, provide technical guidance, and support career development
- Collaborate with stakeholders, product owners, data scientists, and analysts to understand data needs and translate them into engineering solutions
- Build and maintain Power BI data models, semantic layers, and datasets to support self-service analytics and business reporting
- Continuously identify opportunities to optimize pipeline performance, reduce costs, and improve data reliability and quality
- Adhere to and enforce data engineering standards, data security, and governance practices across the platform

Required Skills and Experience:

- 8 to 10 years of experience in data engineering with a strong track record of delivering production-grade data solutions
- Strong proficiency in Python (PySpark, Pandas) and SQL for data transformation, pipeline development, and performance tuning




- Proficient with Microsoft Fabric including Lakehouses, Warehouses, Dataflows Gen2, and Data Pipelines
- Solid experience with SQL Server including schema design, stored procedures, indexing, and query optimization
- Experience with MongoDB and MongoDB Atlas for NoSQL data modeling, indexing, aggregation pipelines, and Atlas Search
- Solid experience designing and operating ETL/ELT pipelines in production, including error handling, monitoring, and SLA management
- Experience with Power BI including dataset design, DAX, semantic modeling, and enabling self-service reporting
- Strong exposure to AI-enabled development — using AI coding assistants, prompt-driven development, or LLM-integrated tooling to build and accelerate data engineering workflows
- Experience leading or managing a small team of engineers — task allocation, mentoring, and performance support
- Good understanding of data modeling concepts — dimensional modeling, star/snowflake schemas, data vault
- Ability to communicate technical ideas clearly to both technical and non-technical audiences

Nice to Have Qualities & Skills

- Hands-on experience with Databricks including Delta Lake, notebooks, jobs, clusters, and Unity Catalog
- Exposure to cloud data services on Azure (preferred), GCP, or AWS
- Experience with streaming and event-driven architectures using Apache Kafka, Azure Event Hubs, Azure Service Bus, or similar queue/messaging technologies
- Exposure to .NET for building data-adjacent services or APIs
- Familiarity with data governance, data cataloging, and data lineage tooling
- Exposure to MLOps or supporting ML pipeline infrastructure
- Exposure to Mortgage or Real Estate domain

Interested ones can share their CV to [email protected]

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