Data Engineer - AWS

Req ID: 366941 

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"

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