NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Data Engineer - AWS to join our team in Remote, Karnātaka (IN-KA), 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.
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Primary Focus (Must-Have Outcome)
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
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Key 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
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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

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client's needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, .

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