Lead Data Engineer - Data Management

Overview

Lead Data Engineer responsible for architecting and maintaining modern, scalable data platforms that power analytics, AI, and decision-making for client organizations.

What you'll do

• Work with client stakeholders to translate business challenges into data architecture requirements and solution roadmaps.
• Design cloud-native data platform architectures including data lakes, lakehouses (Delta Lake, Apache Iceberg), and modern data warehouses.
• Define KPIs, data models, and metrics frameworks aligned with client goals.
• Plan and deliver integration implementations using streaming pipelines and ELT/ETL orchestration for real-time processing.
• Implement AI-ready data infrastructure with governance, lineage, and accessibility patterns.
• Integrate AI tools to accelerate delivery activities such as pipeline development and code reviews.
• Design and deploy MCP servers to expose data platform capabilities for AI agents and LLM workflows.

What you'll need

• 6–9 years of relevant experience in data engineering, data platform development, or cloud data architecture.
• B.E/B.Tech. undergraduate degree from a tier-1 or tier-2 institution.
• Strong SQL skills including query optimization, complex transformations, and data modeling across relational and columnar databases.
• Hands-on experience with at least two of: Microsoft Fabric, Azure Synapse Analytics, Databricks, Snowflake, Google BigQuery, AWS Redshift.
• Experience designing data lake and lakehouse architectures using open table formats (Delta Lake, Apache Iceberg) on cloud storage (ADLS, S3, GCS).
• Proficiency in cloud-native orchestration tools such as Azure Data Factory, Databricks Workflows, dbt, or Apache Airflow.
• Hands-on experience building MCP (Model Context Protocol) servers for AI agents and tools.

Nice to have

• Experience with streaming platforms (Apache Kafka, Azure Event Hubs, AWS Kinesis).
• Working knowledge of BI tools (Power BI, Tableau, Looker).

Details

• Location: Hyderabad, Telangana.