Ashish Arvind Mhatre

Data Platform Modernization and Migration.

• Lead and govern the AI-driven transformation of legacy ETL platforms to modern cloud data ecosystems, ensuring resilience, continuity, and efficiency across enterprise data operations.
• Define and execute multi-phase transformation roadmaps aligned to business criticality, technology currency, and platform strategy.
• Drive adoption of modern data architectures for analytics, data warehousing, and data products.

Architecture and Design Leadership.

• Establish enterprise ETL/ELT reference patterns and implementation standards for data marts and data products, leveraging AWS, Databricks, Snowflake, DBT, and Ab Initio.
• Establish architecture best practices for data ingestion, transformation, orchestration, security, and access management.
• Define and design enterprise-grade, reusable data frameworks on Databricks, Ab Initio, and Snowflake to support ingestion, transformation, encryption, loading, and access governance.
• Evaluate and assess target data platforms for AI-enabled SDLC integration, driving operational efficiency, automation, and engineering productivity.

Data Products and Analytics Enablement.

• Architect and deliver AI-ready data products optimized for BI and analytics consumption, enabling data democratization, and conversational AI.
• Design and implement Qlik dashboards for guided analytics and self-service insights.
• Ensure data platforms support both operational reporting and advanced analytics use cases.

Innovation, POVs, and Accelerators

• Drive technology experimentation and validation through POVs, POCs, and MVPs, enabling informed adoption of modern, AI-enabled data engineering, and visualization stacks.
• Establish reusable accelerators and reference assets to reduce cycle time, minimize rework, and improve delivery predictability.

Collaboration and Stakeholder Engagement.

• Partner with data scientists, analysts, product owners, and business stakeholders to translate business and data needs into scalable, enterprise-grade technical solutions.
• Act as a trusted advisor to leadership, aligning data architecture decisions with business outcomes.
• Collaborate with the platform, security, and infrastructure teams to ensure enterprise compliance and standards.

Leadership and Talent Development.

• Provide strong technical leadership, mentoring, and coaching to data engineering and analytics teams.
• Built and mentored a strong team of over 100 data engineers and specialists, delivering large-scale data and cloud migration programs.
• Foster a culture of engineering excellence, ownership, and continuous learning.

• Comprehending business requirements and transforming them into technical requirements
• Creating and developing processes to streamline development, testing and production implementation
• Creating and publishing EMEA regional release calendar
• Guiding team to develop optimized Ab Initio graphs to cater business requirements
• Generating, modifying and scheduling jobs in Autosys
• Interacting with business and technology stakeholders to successfully implement projects
• Interacting with onsite production support to help analyze and fix the production issues
• Documenting new and/or changed interfaces for cross regional data sharing compliance
• Regional liaison to get Information security and compliance approvals for data sharing outside of Swiss realm
• Establishing controls and Designing solutions to ensure no leakage of SWISS data

• Technology Lead for Fortune 50 Insurance client with 3 years in US
• Leading a team of Ab Initio developers maintaining Datawarehouse and Datamart across multiple subject areas
• Lead a team to upgrade a complex Ab Initio project spanning multiple releases and challenges