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ntt data north america

Data Engineer Advisor

ntt data north america
Pune, India
7-9 Years
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Job Description

Role Overview

We are seeking an Expert Data Engineer with 7+ years of experience in cloud-based data engineering, specializing in Snowflake and AWS ecosystem. The ideal candidate will design, build, and optimize scalable data platforms, enabling advanced analytics and enterprise data modernization.

Key Responsibilities

Data Engineering & Pipeline Development

  • Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue, Snowflake, and SQL-based frameworks
  • Build and manage data ingestion frameworks using APIs, batch, and streaming mechanisms
  • Design efficient data transformation logic using SQL / PL-SQL and Snowflake capabilities
  • Implement incremental and real-time data processing pipelines

Cloud & Data Platform Engineering

  • Develop and maintain cloud-native data platforms leveraging AWS S3, Glue, Redshift/Snowflake integration
  • Architect and optimize data lakes and data warehouses
  • Ensure high performance, cost efficiency, and scalability of data solutions

Snowflake Engineering

  • Design, build, and optimize Snowflake data warehouse solutions
  • Implement data modeling, partitioning, clustering, and performance tuning
  • Work with secure data sharing, governance, and data optimization techniques

Collaboration & Delivery

  • Work closely with business stakeholders, architects, and analytics teams
  • Support end-to-end delivery from design to production deployment
  • Review and optimize existing data architecture and pipelines

More Info

Job Type:
Permanent Job
Industry:
Other
Function:
Data Engineering
Employment Type:
Full time

Job ID: 147869431

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Last Updated: 20-05-2026 05:22:39 PM
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Data Engineer Advisor

NTT Data
Pune, India

Skills:

data warehouses , snowflake , Apis, Sql, ELT, Clustering, Data Modeling, AWS Glue, Aws S3, Performance Tuning, Pl-sql, AWS, Etl, Redshift, real-time data processing, data optimization, data ingestion frameworks, data transformation logic, partitioning, data lakes, data sharing governance