Data Architect - Data Transformation

Data Architect - Data Transformation

Role Purpose -

Lead strategic client engagements, shape large-scale data transformation opportunities, and drive end-to-end solution architecture across data, AI, analytics, governance, and cloud platforms. Act as a trusted advisor to CDO/CDAO organizations and own the technical solutioning for consulting and transformation pursuits.

Key Responsibilities

• Lead client workshops with CDO, CIO, CTO, and Business stakeholders to define enterprise data strategy, target architecture, and transformation roadmaps.
• Own pre-sales solutioning, including opportunity qualification, discovery assessments, architecture visioning, proposal development, and executive presentations.
• Design enterprise-scale data platforms covering data lakes, lakehouses, warehouses, data mesh, metadata management, lineage, governance, MDM, and data quality frameworks.
• Define Data-by-Design controls across the software development lifecycle, ensuring alignment with governance, risk, privacy, and regulatory requirements.
• Shape AI and GenAI-enabled data architectures, including vector databases, knowledge management, semantic layers, RAG architectures, and AI governance frameworks.
• Develop business cases, value realization models, operating models, and transformation roadmaps for executive stakeholders.
• Collaborate with sales, consulting, engineering, and partner ecosystems (Microsoft, AWS, Google Cloud, Databricks, Snowflake, Informatica, Collibra, etc.) to build winning solutions.
• Lead architecture governance and provide strategic guidance throughout the engagement lifecycle from pursuit to delivery.

Must-Have Experience

• 10+ years of experience in Data Architecture, Data Engineering, Analytics, or Digital Transformation.
• Strong experience engaging with CDO/CDAO organizations within Banking and Financial Services.
• Proven track record in winning and delivering large-scale data transformation programs.
• Hands-on expertise in cloud-native data platforms, data modeling, integration, governance, metadata, lineage, and analytics architectures.
• Experience with modern data technologies such as Databricks, Snowflake, Azure Data Platform, AWS Data Services, Fabric, Informatica, Collibra, Alation, or equivalent.
• Strong understanding of regulatory, risk, compliance, and data governance requirements within financial institutions.
• Demonstrated ability to lead executive-level workshops, create proposals, manage RFPs/RFIs, and support sales pursuits.

Enterprise Data Architecture Design

• Define and implement scalable data architecture, data models, and standards aligned with business and technology strategies.

Data Modernization & Transformation

• Lead cloud migration, data platform modernization, data lakehouse, warehouse, and real-time data architecture initiatives.

Business & Stakeholder Consulting

• Engage with business leaders to translate business requirements into data solutions, roadmaps, and architecture blueprints.

Data Governance & Quality

• Establish data governance frameworks, metadata management, lineage, security, privacy, and data quality controls to ensure regulatory compliance.

Technology Leadership & Solution Advisory

• Recommend and evaluate technologies, provide architecture governance, mentor teams, and drive best practices across data engineering, analytics, AI, and reporting ecosystems.

Key Skills

• Enterprise Data Architecture
• Data Strategy & Operating Model Design
• Data Governance, Metadata & Lineage
• Cloud Data Platforms (Azure/AWS/GCP)
• Consulting & Client Advisory
• Pre-Sales, Solutioning & Deal Shaping
• Executive Stakeholder Management
• Banking & Financial Services Domain