Solution Architect - Data Platform Modernization
At a glance
Mid-level Data Engineering role at NTT DATA. Bangalore.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Set the future data-platform design across ingestion, storage, transformation, consumption, security and observability
- Plan migration waves and create architecture diagrams and reusable reference patterns
- Design Databricks workspaces, compute, jobs, Delta Lake layers and connections to Azure services
- Set migration approaches for schemas, SQL logic, batch and incremental loads, and change-data capture
- Build reusable migration tools and define Snowflake ELT layers with dbt
What you bring
- At least fifteen years designing enterprise data platforms and analytics architectures in regulated industries
- Deep experience with Databricks, ADLS or S3, Delta Lake, dbt, orchestration and secure data consumption
- Strong data-modeling experience across policy, claims, billing, customer and reference data
Who this fits
This role suits a senior data-platform architect who can shape migration design and align it with security, governance and enterprise standards. The work spans Databricks and Snowflake, including architecture, migration patterns and reusable frameworks.
From the employer
Roles & Responsibilities:
• Define the end-to-end migration strategy across:
• Own the target state architecture across data ingestion, storage, transformation, consumption, security, and observability.
• Create and maintain high-level and detailed architecture diagrams, migration wave plans, and reference patterns.
• Align architecture with enterprise standards, security, compliance, and cloud governance.
• Design the Databricks architecture: workspaces, clusters, jobs, Delta Lake layers (bronze/silver/gold), and integration with Azure services.
• Define integration patterns with Azure services such as ADLS, ADF/Synapse, Key Vault, Azure DevOps, and monitoring/log analytics.
• Select and standardize data access methods (e.g., external tables, views, direct connections, APIs) for downstream consumers.
• Analyze existing schemas, workloads, and query patterns, and define equivalent or improved implementations in Databricks and Snowflake.
• Define canonical migration patterns for:
o Table structures (including partitioning, clustering, distribution)
o Stored procedures, complex SQL, and business logic
o Batch and incremental loads / CDC
• Design reusable migration frameworks and accelerators (e.g., code templates, parameterized pipelines, data validation utilities).
• Establish a wave-based migration model (by subject area / domain / criticality) with clear entry/exit criteria.
• Define target ELT patterns using dbt on Snowflake (staging, core, mart layers).
Experience :
• 15+ years designing enterprise data platforms, Lakehouse / medallion architectures, and scalable analytics ecosystems in regulated industries.
• Deep experience defining Bronze, Silver, and future Gold / ODS patterns using Databricks, ADLS/S3, Delta Lake, DBT, orchestration, and secure consumption layers.
• Strong capability in canonical data modeling across Policy, Claims, Billing, Customer, and reference/master data domains.
• Experience with architecture decisions for performance, partitioning, lineage, metadata, resilience, disaster recovery, and environment strategy.
• Able to align enterprise standards, security controls, DevSecOps, and future extensibility for AI/ML, self-service analytics, and downstream integrations.
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