AWS Data Engineer

Role - AWS Data Engineer

Exp - 3 to 5 years Work Mode: 5 days WFO

Location: Financial District, Hyderabad Shift Timings: 9:00 AM – 1:00 PM IST (4 hrs in office) and then (8:00 PM – 12:00 AM IST)

About the project: We are expanding our Inter-Sellar Growth and Seller Growth Systems team to support large-scale seller growth initiatives and the increasing demand for scalable data platforms, migration pipelines, and AI-driven insights. The role focuses on designing and building robust data engineering solutions that enable migration from legacy CRM platforms to Salesforce while powering analytics and downstream AI-native applications. This is a high-impact opportunity to work on modern AWS-based data architecture, enterprise-scale migrations, and intelligent data platforms within a fast-paced environment.

Key Responsibilities 1. Architecture & Data Migration

• Design and develop end-to-end migration pipelines using AWS services such as S3, Glue, Redshift, and Lambda.
• Support migration of large-scale datasets from legacy CRM systems into Salesforce.
• Leverage internal tools and frameworks to ensure scalable and reliable migration workflows.

2. Pipeline Engineering

• Build scalable, maintainable, and high-performance ETL/ELT pipelines for structured and unstructured data.
• Optimize batch processing and data transformation workflows.
• Improve pipeline reliability, reusability, and operational efficiency.

3. Data Modeling & Warehousing

• Design and implement optimized data models in Redshift and Salesforce environments.
• Apply dimensional modeling techniques including Star and Snowflake schemas.
• Enable analytics, reporting, and AI-driven applications through efficient warehouse design.

4. Cross-Functional Collaboration

• Work closely with Software Development Engineers, BIEs, Product Managers, and Analytics teams.
• Gather business and technical requirements and convert them into scalable engineering solutions.
• Participate in architecture discussions, technical reviews, and delivery planning.

5. Operational Excellence

• Implement monitoring, alerting, data quality validation, and error-handling frameworks.
• Ensure high levels of data accuracy, consistency, and governance during migration cycles.
• Drive automation and operational best practices across the data platform.

Mandatory Requirements

• 3+ years of professional experience in Data Engineering with strong exposure to large-scale data migrations.
• Strong SQL expertise with ability to write highly optimized and complex queries for deep-dive analysis.
• Hands-on experience with:
• AWS Redshift
• S3
• AWS Glue
• AWS Lambda
• Strong programming skills in Python (preferred) or Java/Scala.
• Experience with ETL/ELT frameworks and legacy migration tools such as Informatica or SSIS.
• Strong understanding of:
• Data Warehousing concepts
• Dimensional Modeling
• Star/Snowflake schemas
• Experience reverse-engineering undocumented or legacy systems and building migration strategies.

Preferred Qualifications

• Experience with Salesforce integrations including:
• Salesforce Data Loader
• Bulk API
• AWS-to-Salesforce data flows
• Experience building dashboards using QuickSight or Tableau for migration validation and data parity tracking.
• Experience working on legacy analytical platform modernization initiatives.
• Exposure to AI-assisted engineering solutions, including:
• AI agents for code refactoring
• Automated code migration frameworks
• AI-native data applications