Data Engineering Architect

Data Engineering Architect

Company: LTIMindtree

Role: Data Engineering Architect

Location: Hyderabad

Experience: 11–15 Years

Salary: Up to 29 LPA

Notice Period: Immediate Joiners Only

Work Location Requirement: Candidates currently based in Hyderabad only

Job Summary

We are seeking an experienced Data Engineering Architect to lead the transformation of our existing data engineering and analytics ecosystem into a scalable, product-oriented Data Platform organization. The ideal candidate will define architecture standards, modernize the data stack, establish governance frameworks, and enable self-service analytics capabilities across the enterprise.

This role requires a highly hands-on technical leader with deep expertise in Snowflake, AWS, Python, enterprise data modeling, and scalable analytics platforms.

Key ResponsibilitiesArchitecture & Technical Leadership

• Define and own end-to-end data platform architecture using Snowflake as the core data warehouse
• Design scalable batch, streaming, and real-time data systems on AWS
• Drive adoption of modern architectures including Lakehouse, Data Mesh, and Snowflake-native patterns
• Establish standards for logical and physical data modeling and semantic layers
• Develop enterprise-level Logical Data Models (LDM) aligned with business domains
• Lead architecture reviews and technical decision-making

Hands-on Engineering

• Design and implement critical platform components using Python and Snowflake
• Build and optimize ELT pipelines, streams, tasks, and query performance in Snowflake
• Review schemas, transformations, and analytics models
• Troubleshoot and optimize pipeline and query performance

Data Platform & Analytics Enablement

• Architect scalable pipelines for structured and unstructured data
• Develop reusable and governed data products
• Enable self-service analytics and BI integrations
• Support real-time and near real-time analytics workloads
• Integrate with BI tools such as Tableau, Power BI, and Looker

Governance, Security & Operational Excellence

• Establish data governance, lineage, and cataloging frameworks
• Implement data quality and validation pipelines
• Define secure access controls and auditing mechanisms
• Define SLAs/SLOs for platform reliability and performance
• Optimize Snowflake cost and platform scalability

Leadership & Collaboration

• Mentor engineering and analytics teams
• Collaborate with business stakeholders and product teams
• Translate business requirements into scalable technical solutions
• Act as the technical authority for enterprise data architecture

Required SkillsMandatory Skills

• Snowflake Architecture & Performance Tuning
• AWS (S3, Glue, Lambda, EMR, Redshift)
• Python
• SQL & ETL/ELT Frameworks
• Enterprise Data Modeling (LDM, Dimensional Modeling, Data Vault)
• Batch & Real-Time Data Processing
• Spark / Distributed Processing
• BI Tools – Tableau, Power BI, Looker
• Data Governance, Security & Compliance