Technology and Transformation - Engineering - Manager - AWS Solution Architect - Bengaluru

Technology and Transformation - Engineering - Manager - AWS Solution Architect - Bengaluru
• Job requisition ID : 105387 
• Location: Bengaluru
• Entity: Deloitte Touche Tohmatsu India LLP 

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. 

Your work profile

The Lead Solution Architect is responsible for leading end-to-end architecture, design and solutioning for enterprise-scale cloud transformation and data modernization initiatives in the BFSI domain, with a strong focus on AWS cloud-native platforms, Databricks and modern data architecture.This role works closely with business stakeholders, product owners, engineering teams, enterprise architects, DevOps teams and client stakeholders to translate business requirements into scalable, secure, resilient and cost-effective technical solutions.

Key Skills & Competencies

• Lead end-to-end architecture, design and solutioning for enterprise-scale cloud transformation and data modernization initiatives in the BFSI domain.
• Design scalable, secure, resilient and high-performing cloud-native architectures on AWS.
• Collaborate with business stakeholders, product owners, engineering teams and enterprise architects to translate business requirements into technical solutions.
• Define architecture standards, best practices, governance models and reusable frameworks for AWS and Databricks-based data platforms.
• Drive architecture review discussions, technical estimations, risk assessments and solution roadmaps.

• Design and implement enterprise data lake, lakehouse and modern analytics architectures using AWS and Databricks.
• Lead technical solutioning for large-scale ETL/ELT pipelines, real-time streaming, batch processing and data integration solutions.
• Design reusable data components and frameworks using AWS and Databricks technologies.
• Optimize AWS infrastructure, Databricks workloads and data processing pipelines for performance, scalability, reliability and cost efficiency.
• Ensure solutions are aligned with BFSI security, regulatory, governance and data privacy standards.

• Provide technical leadership, mentorship and guidance to development and engineering teams.
• Work closely with DevOps and infrastructure teams for CI/CD automation, deployment strategies, monitoring and observability.
• Support pre-sales activities including technical proposals, architecture presentations and client discussions.
• Lead multiple initiatives in a fast-paced environment while maintaining architecture quality and governance discipline.
• Create strong documentation, architecture artefacts, presentations and solution governance materials for technical and business audiences.
• Strong understanding of AWS cloud architecture, distributed systems, data warehousing and modern data platform concepts.
• Extensive hands-on experience in AWS cloud services and cloud-native solution design for enterprise-grade applications and data solutions.
• Strong hands-on expertise in AWS Glue, Amazon S3, AWS Lambda, AWS Lake Formation, Amazon Athena and Amazon EventBridge.
• Strong hands-on experience in Databricks, PySpark, Spark ecosystem, Spark DataFrames, RDDs and SparkSQL.
• Expertise in PySpark performance optimization and distributed data processing techniques.
• Experience in Hadoop ecosystem, modern big data platforms and scalable ETL/ELT pipeline design.
• Expertise in advanced SQL and PL/SQL programming with strong understanding of enterprise data warehouse concepts.
• Strong experience with Amazon Athena, AWS Glue Catalog, Databricks and reusable data engineering frameworks.
• Experience with GitLab Actions or similar CI/CD tools, DevOps practices, Infrastructure-as-Code, automated deployments and release management.
• Strong stakeholder management, client-facing communication, problem-solving, analytical, leadership and mentoring capabilities.
• Cloud and architecture: AWS cloud architecture, distributed systems, enterprise solution architecture, cloud-native design and architecture governance.
• AWS technology stack: AWS Glue, Amazon S3, AWS Lambda, AWS Lake Formation, Amazon Athena and Amazon EventBridge.
• Databricks skills: Databricks lakehouse architecture, Databricks workflows, Spark processing, notebooks, clusters and production data engineering patterns.
• Data engineering and big data: PySpark, Spark DataFrames, RDDs, SparkSQL, Hadoop ecosystem and distributed data processing.
• Modern data platforms: Enterprise data lake, lakehouse, data warehouse, modern analytics architecture and data integration design using AWS and Databricks.
• Database and SQL: Advanced SQL, PL/SQL, Amazon Athena, AWS Glue Catalog and enterprise data warehouse concepts.
• DevOps and CI/CD: GitLab Actions or similar CI/CD tools, Infrastructure-as-Code, automated deployment and release management.
• BFSI domain alignment: Security, regulatory, governance, data privacy and compliance-oriented architecture design.
• Solution leadership: Technical estimations, risk assessments, architecture roadmaps, design reviews and reusable architecture frameworks.
• Client-facing skills: Strong stakeholder management, architecture presentations, proposal support and executive communication.
• Leadership competencies: Mentoring, documentation, analytical problem-solving, governance discipline and ability to lead multiple initiatives.
• Proficiency in English is required.

Preferred Qualifications

• Education - B. tech / BE in Computer Science or Information Technology.

Success Metrics

• High-quality AWS and Databricks-based data architecture solutions delivered in alignment with business, regulatory and technology requirements.
• Successful delivery of scalable, secure, resilient and cost-optimized AWS cloud-native architectures.
• Reusable architecture standards, governance models and AWS/Databricks data platform frameworks adopted across teams.
• Improved performance, reliability, observability and cost efficiency of AWS infrastructure, Databricks workloads and data processing pipelines.
• Effective stakeholder engagement, client-facing solutioning and successful support for proposals and architecture presentations.
• Strong technical leadership, mentoring outcomes and consistent architecture governance across engineering teams.

Location and way of working:

• Base location: Bengaluru / Pune
• This profile involves travelling to client locations