Lead Solution Cloud Architect

About the Role EXL Service is seeking an accomplished Data (DBX) Leader with 12–15 years of progressive experience in designing, implementing, and governing enterprise cloud and data architectures. The ideal candidate brings deep expertise in AWS and Databricks , with strong architectural leadership capabilities from Banking and Financial domain . Exposure to Azure cloud services is a significant advantage. This is a senior/lead role responsible for shaping cloud strategy, guiding engineering teams, and ensuring that solutions meet enterprise standards for scalability, security, performance, and cost-efficiency. Key Responsibilities: Cloud & Data Architecture Architect and design enterprise-grade cloud solutions leveraging AWS services (EC2, S3, Glue, Lambda, Kinesis, IAM, Redshift, EMR). Design Databricks Lakehouse solutions including Delta Lake, Unity Catalog, Spark optimization, governance, and MLOps patterns. Build scalable ETL/ELT pipelines, real-time streaming architectures, and reusable data integration frameworks. Develop high-level and low-level architecture blueprints ensuring security, compliance, cost efficiency, reliability, and performance. (Preferred) Architect cloud/on-prem hybrid data platforms using Azure services such as Azure Data Lake, ADF, Azure Databricks, Synapse, etc. Solution Design & Delivery - Lead requirement discovery, translate business needs into robust architectural designs and roadmaps. Create HLDs, LLDs, data flow diagrams, integration patterns, deployment models, and security reference architectures. Oversee end-to-end delivery, guiding engineering and DevOps teams through implementation and optimization. Perform architecture assessments and recommend improvements for scalability, resilience, and cost savings. Technical Leadership - Provide thought leadership and hands-on direction to data engineering, analytics, DevOps, and platform teams. Establish best practices for coding, data governance, CI/CD, infrastructure automation, and environment management. Introduce and evaluate emerging cloud technologies, tools, and frameworks relevant to analytics and modern data platforms. Stakeholder & Client Management Good in client engagement and Act as technical SME for client conversations, workshops, and executive presentations. Communicate complex architectural concepts clearly to both technical and non-technical audiences. Partner closely with business stakeholders to define solution vision, roadmap, and success metrics. Required Skills & Experience: Technical Expertise 12–15 years of overall IT experience with strong focus on cloud, data engineering, and enterprise architecture in Banking and Financial domain . 5+ years of hands-on experience architecting production solutions on AWS. 3+ years’ strong experience in Databricks (Spark, Delta Lake, MLflow, Unity Catalog). Proficiency in Python, SQL, PySpark, and distributed data processing frameworks. Deep understanding of data modeling, data governance, metadata management, and modern security practices. Experience with CI/CD pipelines, Terraform / CloudFormation, GitOps, and end-to-end automation. Strong knowledge of cloud networking, VPCs, IAM, encryption, identity governance, and security frameworks (NIST, CIS benchmarks). (Preferred) Experience with Azure cloud architecture, including Azure Databricks, ADF, ADLS, Synapse, and Azure DevOps. Base Compensation Range: $140,000-$170,000 The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process. Key Responsibilities Cloud & Data Architecture Architect and design enterprise-grade cloud solutions leveraging Azure services (Azure Virtual Machines, Azure Blob Storage, Azure Data Factory, Azure Functions, Azure Event Hubs, Azure Active Directory and Azure Synapse Analytics). Design Databricks Lakehouse solutions including Delta Lake, Unity Catalog, Spark optimization, governance, and MLOps patterns. Build scalable ETL/ELT pipelines, real-time streaming architectures, and reusable data integration frameworks. Develop high-level and low-level architecture blueprints ensuring security, compliance, cost efficiency, reliability, and performance. Architect cloud/on-prem hybrid data platforms leveraging the full Azure ecosystem including Azure Data Lake Storage, Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Purview, and Azure DevOps. Solution Design & Delivery Lead requirement discovery, translate business needs into robust architectural designs and roadmaps. Create HLDs, LLDs, data flow diagrams, integration patterns, deployment models, and security reference architectures. Oversee end-to-end delivery, guiding engineering and DevOps teams through implementation and optimization. Perform architecture assessments and recommend improvements for scalability, resilience, and cost savings. Technical Leadership Provide thought leadership and hands-on direction to data engineering, analytics, DevOps, and platform teams. Establish best practices for coding, data governance, CI/CD, infrastructure automation, and environment management. Introduce and evaluate emerging cloud technologies, tools, and frameworks relevant to analytics and modern data platforms. Stakeholder & Client Management Act as technical SME for client conversations, workshops, and executive presentations. Communicate complex architectural concepts clearly to both technical and non-technical audiences. Partner closely with business stakeholders to define solution vision, roadmap, and success metrics. 12–15 years of overall IT experience with strong focus on cloud, data engineering, and enterprise architecture. 5+ years of hands-on experience architecting production solutions on Microsoft Azure. 5+ years’ strong experience in Databricks (Spark, Delta Lake, MLflow, Unity Catalog).