Snowflake Arch/Engineer

NTT DATA North America

Pune Division, Maharashtra, India1d agovia LinkedIn

About the Role

NTT DATA is seeking a Snowflake Arch/Engineer to join their team.

Key Responsibilities

  • Own and evolve the Snowflake data platform architecture for Finance Corporate Services.
  • Design scalable, secure, and high-performance data models (dimensional, ELT/ETL patterns).
  • Define best practices for:
  • Data ingestion (batch & near real-time)
  • Data transformation and modeling
  • Data security, governance, and access controls
  • Partner with global architecture teams to align with enterprise data strategy.
  • Lead offshore teams in design, development, and deployment of Snowflake-based solutions, driving the end-to-end delivery lifecycle (SDLC Phases): Requirements analysis, Design & build, Testing (SIT/UAT), Release management.
  • Oversee development of ELT pipelines (ADF / Databricks / similar) and Data marts for Finance (GL, Subledger, Reporting), ensuring adherence to coding standards, performance optimization, and reusability.
  • Oversee data pipeline and integration from multiple source systems (e.g., GL, Treasury, Advisory, etc.).
  • Manage dependencies across Upstream systems (databases, source apps) and Downstream consumers (BI / reporting tools), ensuring data reconciliation, completeness, and accuracy across systems.
  • Ensure adherence to Data governance standards, including:
  • Audit and regulatory requirements
  • SDLC and change management processes
  • Implementing data lineage, controls, and reconciliation frameworks

Requirements & Tech Stack

  • Snowflake
  • Data modeling
  • ELT/ETL patterns
  • Data ingestion
  • Data transformation
  • Data security, governance, and access controls
  • ELT pipelines (ADF / Databricks / similar)
  • Data marts
  • BI / reporting tools
  • Data lineage
  • SDLC Phases
  • Testing (SIT/UAT)
  • Release management
  • Coding standards
  • Performance optimization
  • Reusability
  • Data reconciliation
  • Data completeness
  • Data accuracy
  • Audit and regulatory requirements
  • Change management processes
  • Data governance standards

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