NTT Data Work from Home Jobs; Hiring Data Engineer (AWS) – Apply Now

Data Engineer – AWS Job Openings in India 2026!!!

NTT Data announced job vacancy for the post of Data Engineer - AWS. The place of posting will be at Remote (Work from Home) – Hiring Office in Bangalore. Candidates who have completed Graduate / Engineering / Post Graduate with Fresher / Experience are eligible to apply. More details about qualifications, job description and roles & responsibilities are as follows

Company Overview

Name of the Company	NTT Data
Required Qualifications	Graduate
Skills	Amazon S3, Redshift, IAM, CloudWatch
Category	Technology
Work Type	Remote

They 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 Details

Θ Positions: Data Engineer - AWS

Θ Job Location: Remote (Work from Home) – Hiring Office in Bangalore

Θ Salary: As per company standards

Θ Job Type: Full Time

Θ Requisition ID: 366941

Roles and Responsibilities:

• Salesforce to AWS Data Pipelines (Core)
• 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

SQL Engineering (Oracle + Redshift)

• 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

ETL/ELT, Data Modeling, and Warehousing

• 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

Data Quality, Governance, and Compliance

• 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)

Operations, Monitoring, and Reliability

• 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)

Cross-Functional Collaboration

• 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

Required Skills & Qualifications:

• Technology Stack (Expected Exposure)
• Primary (Must-Have)
• 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)
• Data Engineering & Platform (Good-to-Have / 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
• Minimum Skills Required: Required Skills & Experience
• Strong hands-on experience building ETL/ELT pipelines in cloud environments
• Proven experience integrating Salesforce data into a data platform (extraction, S3 landing, transformat"

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