AWS Data Engineer
NTT DATA Services Bangalore, Karnataka, India
IT Services and IT Consulting · 10,001+ employees
About the role
The AWS Data Engineer will design, build, and maintain event-driven data pipelines to move and transform policy data into the Aurora-based Policy Master. They are responsible for ensuring data accuracy, performance, and recoverability while supporting the ingestion-to-serving lifecycle.
What they look for
Requirements
Candidates must have 5-7 years of data or backend engineering experience, with at least 3 years of hands-on AWS development. Proficiency in Python, SQL, and serverless integration patterns like Lambda and SQS is required.
Full description
Req ID: 386157
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 AWS Data Engineer to join our team in Bangalore, Karnātaka (IN-KA), India (IN).
1 | Position Overview
The AWS Data Engineer will design, build, test, and support event-driven policy-data pipelines that move landed files and events through validation, buffering, transformation, and persistence into the Aurora-based Policy Master. Working within established architecture and data-model standards, the engineer will develop secure and reusable components using S3, Lambda, SQS, EventBridge, Python or Java, SQL, and AWS monitoring services. The role is accountable for data accuracy, idempotent processing, lineage, reconciliation, performance, recoverability, and production support across the ingestion-to-serving lifecycle.
2 | Required Skills and Experience
- 5–7 years of data-engineering or backend-engineering experience, including at least 3 years of hands-on development on AWS.
- Strong hands-on experience with AWS S3, Lambda, SQS, EventBridge, CloudWatch, IAM, KMS, Secrets Manager, and related serverless integration patterns.
- Proficiency in Python; Java experience is valuable. Strong SQL skills and practical experience developing against PostgreSQL or Amazon Aurora PostgreSQL.
- Experience building event-driven and batch ingestion pipelines, schema validation, transformations, canonical data mappings, error handling, retry, dead-letter queues, replay, idempotency, and audit logging.
- Strong understanding of JSON and relational data structures, data contracts, schema evolution, reference data, data quality rules, reconciliation, lineage, and metadata capture.
- Experience writing unit and integration tests and using Git-based development, code review, CI/CD pipelines, automated deployment, and environment-specific configuration.
- Working knowledge of API-driven data consumption, REST or OpenAPI contracts, authentication and authorization, and collaboration with microservices teams.
- Ability to troubleshoot distributed workloads using logs, metrics, traces, CloudWatch dashboards, and correlation identifiers; familiarity with performance and cost optimization.
- Understanding of secure cloud engineering including least-privilege IAM, encryption in transit and at rest, VPC integration, secrets management, and protection of sensitive policy data.
- Experience with insurance policy data, policy administration platforms such as OIPA, mainframe feeds, canonical insurance models, or operational data stores is preferred; AWS Developer or Data Engineer certification is an advantage.
3 | Duties
- Develop ingestion components that receive landed policy data in S3 and perform file, event, schema, completeness, and business-rule validation.
- Build Lambda and SQS processing patterns with appropriate message visibility, batching, ordering where required, retry, dead-letter handling, replay, and duplicate-event protection.
- Implement transformations from source-specific policy feeds into the approved canonical Policy Master structure, preserving source lineage and effective-dated history where required.
- Write optimized SQL and data-access logic to load Aurora PostgreSQL while maintaining referential integrity, transaction control, auditability, and high-throughput processing.
- Develop reconciliation controls across source, landing, transformed, and target data, including record counts, control totals, reject reporting, and explainable exception handling.
- Create automated unit, component, and integration tests and participate in peer reviews to ensure code quality, security, maintainability, and adherence to engineering standards.
- Instrument pipelines with structured logging, metrics, alerts, trace or correlation IDs, and operational dashboards; ensure failures are observable and recoverable.
- Partner with the data modeler, solution architect, API engineer, DevSecOps engineer, test engineer, and policy SMEs to refine stories, mappings, contracts, and acceptance criteria.
- Support CI/CD deployment and infrastructure configuration, diagnose issues across development through production, and contribute to runbooks and support procedures.
- Tune Lambda, SQS, Aurora interactions, data access, and processing patterns for performance, resilience, concurrency, and cost while meeting defined service levels.
- Participate in production-readiness reviews, cutover, hypercare, incident resolution, root-cause analysis, and remediation of defects or technical debt.
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, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.
NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.
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