Senior AWS Engineer

Fractal; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Fractal is seeking a Senior Data Engineer (AWS) to design, implement, test, and optimize data ingestion, transformation, and analytics across the ADC platform. You will build scalable data pipelines using AWS-native services, ensure data quality and governance, and enable trusted, query-ready data for reporting and NLP insights.

The role collaborates with data architects, senior engineers, and DevOps to deliver reliable data flows across development and UAT environments, while optimizing

Qualifications

• Hands-on experience with AWS data engineering services
• Strong data modeling expertise
• Solid understanding of distributed data processing patterns

Responsibilities

• Data Ingestion & Pipeline Engineering: Develop data ingestion workflows using AWS Glue, Glue Crawlers, Lambda, S3, EventBridge, and Redshift Serverless.
• Data Warehousing & Modeling: Build and maintain data models in Amazon Redshift and optimize COPY operations and partitioning.
• Data Governance & Quality: Maintain metadata with AWS Glue Data Catalog and support governance via Lake Formation; ensure data quality checks.
• Analytics & NLP Enablement: Enable QuickSight for self-service analytics and NLP-driven queries; model datasets for NLP use cases.
• Monitoring & Operational Excellence: Use CloudWatch to monitor pipelines, perform root-cause analyses, and write runbooks and deployment procedures.

Job description

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

Role Overview

We are seeking a highly motivated Senior Data Engineer (AWS) to support the design, implementation, testing, and optimization of data ingestion, transformation, and analytics capabilities across the ADC platform. The role will focus on building reliable, scalable, and high-performance data pipelines leveraging AWS-native data services while ensuring data quality, governance, and operational excellence.

The ideal candidate will possess hands-on experience with AWS data engineering services, strong data modeling expertise, and a solid understanding of distributed data processing patterns. This role will work closely with data architects, senior engineers, DevOps teams, and business stakeholders to enable trusted, query-ready data for reporting, analytics, and NLP-driven insights.

Key Responsibilities

Data Ingestion & Pipeline Engineering

• Develop, configure, and support data ingestion workflows using AWS Glue, Glue Crawlers, AWS Lambda, Amazon S3, Amazon EventBridge, and Amazon Redshift Serverless.
• Execute ingestion testing activities and validate data movement across raw, curated, and consumption layers.
• Monitor and support schema discovery, schema inference, and schema drift resolution processes.
• Troubleshoot and resolve data pipeline issues, event sequencing failures, and ingestion bottlenecks.
• Collaborate with senior engineers to maintain stable and reliable data flows across Development and UAT environments.

Data Warehousing & Modeling

• Implement and maintain data models within Amazon Redshift to support reporting, analytics, and NLP-driven query capabilities.
• Optimize Redshift COPY operations, data loading strategies, partitioning, and performance tuning processes.
• Support normalization, transformation, and enrichment activities to improve data consistency and usability.
• Ensure datasets are query-ready for downstream business intelligence and AI-driven consumption.

Data Governance & Quality

• Maintain metadata integrity through AWS Glue Data Catalog and support governance processes using AWS Lake Formation.
• Implement and enhance data quality validation checks and reconciliation mechanisms.
• Ensure adherence to data governance, security, and access control standards.
• Monitor and improve data lineage, catalog accuracy, and data discoverability.

Analytics & NLP Enablement

• Support implementation and configuration of Amazon QuickSight to enable self-service analytics and NLP-based querying capabilities.
• Collaborate with Platform and DevOps teams on QuickSight setup, dataset modeling, security integration, and NLP feature enablement.
• Ensure analytics datasets are optimized for performance, accuracy, and business consumption.

Monitoring & Operational Excellence

• Analyze application and pipeline behavior using Amazon CloudWatch Logs and monitoring tools.
• Support incident analysis, root cause investigations, and performance improvement initiatives.
• Contribute to operational documentation, runbooks, deployment procedures, and support guides.
• Promote reproducibility, automation, and engineering best practices across the data platform.

Mandatory AWS

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!