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NTT DATA Logo NTT DATA · IT - Software Development

Data Engineer - AWS

India, Pune · Job Posted June 14, 2026
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Job Description

We are currently seeking a Data Engineer - AWS to join our team in Pune, Mahārāshtra (IN-MH), India (IN). Job Duties: Role Overview We are looking for a skilled Data Engineer to design, build, and maintain scalable, reliable data pipelines and platforms that support analytics, reporting, and operational decision-making. The role’s primary focus is enabling an end-to-end data ingestion and processing pipeline—extracting data preferably from Salesforce, landing it in Amazon S3, and transforming/loading it into Amazon Redshift for analytics-ready consumption. The engineer will also work on SQL modernization (including Oracle SQL development and conversion/optimization for Redshift), data quality, governance, monitoring, and performance tuning.

Job Responsibility

  • Build and operate robust ETL/ELT pipelines for Salesforce → Amazon S3 → Amazon Redshift
  • Automated extraction, secure landing, transformation, load, and publishing for reporting/analytics
  • Strong data quality, reconciliation, monitoring, and scheduling built into the pipeline
  • Build and maintain pipelines that extract data from Salesforce (API-based or connector-based), land data in Amazon S3, and load into Amazon Redshift
  • Implement incremental loads / CDC patterns where applicable
  • manage full loads and historical backfills as needed
  • Establish scheduling and orchestration for daily/near-real-time jobs with reliability and retry mechanisms
  • Design, develop, and optimize complex SQL in Oracle
  • Analyze and convert Oracle SQL to Redshift-compatible SQL, optimizing for Redshift performance and cost
  • Tune Redshift queries using best practices such as sort keys, distribution styles, and query patterns
  • Design and maintain ETL/ELT jobs, transformations, and reusable frameworks
  • Build and optimize data models for warehousing/lakehouse patterns (facts/dimensions, curated layers)
  • Support both batch and (where applicable) near-real-time processing patterns
  • Implement data quality checks (completeness, accuracy, consistency), reconciliation, and validation rules
  • Ensure data integrity, metadata documentation, lineage, and governance practices
  • Apply security and compliance standards (GDPR/regulatory needs where applicable)
  • Monitor pipelines and infrastructure using AWS monitoring tools
  • troubleshoot performance and reliability issues
  • Improve pipeline resilience through alerting, logging, retries, and error handling
  • Contribute to modernization and cloud migration initiatives and automation (DataOps/CI-CD where relevant)
  • Partner with analytics/reporting and business stakeholders to gather requirements and deliver reliable datasets
  • Work effectively with cross-functional teams and provide clear documentation of pipelines and datasets

Requirements

  • Strong hands-on experience building ETL/ELT pipelines in cloud environments
  • Proven experience integrating Salesforce data into a data platform (extraction, S3 landing, transformat)
  • AWS: Amazon S3, Redshift, IAM, CloudWatch
  • Salesforce Integration: Salesforce APIs / connectors (extraction & ingestion patterns)
  • Programming & Querying: Python, SQL
  • Oracle: Complex SQL, stored procedures (as needed), performance tuning
  • Orchestration/Scheduling: AWS Glue, Lambda, Step Functions, cron-based scheduling (or equivalent)

Nice to have

  • ETL tools: Informatica, Talend, Azure Data Factory
  • Warehousing: Snowflake, Azure Synapse (plus Redshift as primary)
  • Big data: Spark, Hadoop
  • Streaming & APIs: Kafka, Event Hub, REST APIs
  • DevOps/DataOps: CI/CD for data pipelines, infrastructure-as-code exposure
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