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Job details:
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
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