Data & Analytics Solutions Architect

14+ years of experience in Enterprise Data Architecture, Azure Data Platforms, Databricks, Data Engineering, and Cloud Modernization.

Proven experience in Enterprise Solution architecture using Azure, Databricks and related technology components across the Data to Insights end to end value chain.

Strong hands-on expertise in Azure Data Services, Azure Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL.

Proven experience designing and implementing Lakehouse Architectures, enterprise data platforms, and modern analytics solutions.

Strong understanding of Databricks Data Intelligence Platform, including Databricks SQL, Workflows, Lakeflow, MLflow, Unity Catalog, Serverless, and Performance Optimization.

Experience building AI-enabled analytics solutions using Databricks Genie, natural language analytics, semantic models, and governed data access patterns.

Expertise in Data Engineering including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata, lineage, observability, and DataOps practices.

Strong knowledge of Enterprise Data Architecture, including data models, data products, lakehouse and warehouse patterns, semantic layers, and master/reference data management.

Experience implementing Security, Governance, and Compliance controls including IAM/RBAC, encryption, privacy, masking, auditability, retention, and responsible AI practices.

Proven experience leading architecture definition, HLD/LLD preparation, NFR assessment, migration planning, technical governance, and production readiness activities.

Experience supporting cloud transformation initiatives, solutioning, RFP responses, effort estimation, and client-facing architecture discussions.

Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.

Preferred certifications in Azure Solutions Architecture, Azure Data Engineering, Databricks, Data Management, Enterprise Architecture, Security, or AI/ML.

Roles & Responsibilities

Engage with business and technology stakeholders to understand data, analytics, AI, and cloud transformation requirements.

Define end-to-end architecture for Azure Databricks-based data, analytics, and AI platforms.

Design scalable, secure, and high-performance Lakehouse solutions using Azure Data Services, Azure Databricks, Delta Lake, and Unity Catalog.

Architect data ingestion, integration, batch, streaming, and data engineering solutions supporting enterprise analytics and AI use cases.

Design and implement AI-enabled analytics solutions using Databricks Genie, semantic models, and governed data access frameworks.

Establish data governance, security, metadata, lineage, observability, and responsible AI standards across the platform.

Lead data platform modernization, migration, and cloud transformation initiatives on Azure.

Define architecture standards, reusable frameworks, best practices, and DataOps delivery models.

Provide technical leadership across solution design , implementation, testing, migration, deployment, and production support activities.

Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices.

Drive platform performance optimization, reliability improvements, and cost optimization across Azure and Databricks environments.

Collaborate with data engineers, AI specialists, architects, platform teams, and client stakeholders to deliver enterprise-scale solutions.

Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops.

Mentor architects and engineers and contribute to capability development, technical assessments, and knowledge-sharing initiatives.

Develop reusable accelerators, reference architectures, implementation frameworks, and best practices for Azure Databricks and AI solutions.

Generic Managerial Skills, If any

Strong leadership and stakeholder management skills with the ability to work effectively across business, data, engineering, and architecture teams.

Excellent communication and presentation skills for technical, business, and executive audiences.

Strong consulting and problem-solving mindset with the ability to evaluate options and recommend practical solutions.

Proven ability to lead cross-functional and distributed teams while driving collaboration and delivery outcomes.

High ownership, accountability, and attention to detail with a focus on quality and customer success.

Strong planning, prioritization, and decision-making skills while managing multiple initiatives and stakeholders.

Experience mentoring architects and engineers and promoting engineering best practices.

Ability to proactively manage risks, dependencies, and escalations throughout the project lifecycle.

Strong client-facing experience supporting workshops, architecture reviews, solution presentations, and executive discussions.

Adaptability to work in fast-paced environments with evolving business priorities and technology landscapes.