Senior Cloud Architect

EXL Service is seeking an accomplished Lead Solution Cloud Architect with 12–15 years of progressive experience in designing, implementing, and governing enterprise cloud and data architectures. The ideal candidate brings deep expertise in Azure with strong architectural leadership capabilities. Experience with Azure Databricks will be a significant advantage.

Key Responsibilities

• Define and own the end-to-end Azure data & analytics architecture aligned to business and modernization goals
• Lead migration strategy from legacy/on-prem (e.g., SAS, Hadoop, EDW) to Azure ecosystem
• Establish architecture standards, governance frameworks, and design patterns
• Drive cost optimization, performance efficiency, and scalability across the platform
• Ensure data security, compliance, and access governance across all layers
• Collaborate with engineering teams to ensure high-quality, production-grade delivery

Solution Design & Delivery

• Design and implement modern data platform architectures using:
• ADLS Gen2 (Bronze/Silver/Gold layers)
• Azure Synapse (Serverless & Dedicated SQL Pools)
• Azure Data Factory / Synapse Pipelines
• Define data ingestion patterns (batch, incremental, CDC where applicable)
• Architect SQL-centric transformation strategies for faster migration from legacy systems
• Design data modeling approaches (dimensional, snapshot facts, SCD2, campaign analytics models)
• Optimize file formats, partitioning, and storage strategies (Parquet/Delta best practices)
• Ensure performance tuning across compute (Spark/SQL) and storage layers
• Guide CI/CD, DevOps, and environment promotion strategies

Technical Leadership

• Provide hands-on architectural guidance to data engineers and platform teams
• Define best practices for coding, orchestration, and data processing
• Mentor teams on Azure-native services vs alternative tools (e.g., Databricks)
• Lead POCs, MVP execution, and technology evaluations
• Drive design reviews, architecture governance, and solution validation
• Ensure reusability, modular design, and reduced technical debt

Stakeholder & Client Management

• Act as the primary technical advisor to business and client stakeholders
• Translate business requirements into scalable technical solutions
• Present architecture proposals, trade-offs, and roadmap strategies to leadership
• Work closely with data, analytics, and campaign teams to align on use cases
• Support delivery planning, estimation, and risk management
• Drive alignment between platform, engineering, and business teams

Required Skills & Experience

Strong hands-on experience in Azure Data Ecosystem:

• Azure Data Factory (ADF) / Synapse Pipelines
• Azure Synapse Analytics (Serverless & Dedicated SQL Pools)
• ADLS Gen2 (data lake architecture & optimization)

Expertise in SQL-centric data processing and optimization

Proficiency in PySpark, Python, and SQL

Experience with Spark-based transformations (Synapse Spark Pools)

strong experience in Ingestion frameworks and reusable pipeline design

Expertise in Query tuning (SQL & Spark) & Cost-performance trade-offs (Serverless vs Dedicated vs Spark)

Nice to Have Skills :

Exposure to Azure Databricks (future adoption readiness)

Experience with modern data stack tools (DBT, Fivetran, orchestration frameworks)

Experience

• 12–15 years in data engineering / data architecture
• Proven experience in leading large-scale cloud data transformations
• Strong background in stakeholder management and solution leadership