Data Engineer

Role: Data engineer

Location: Hyderabad, India

Level: Mid to Senior

Exp: 4 to7 Years

Mode :WFO(5 days)

Role Overview

As a Data Engineer within the Amazon FinTech organization, you will play a critical role in automating and scaling the financial systems that power Amazons global operations. You will focus on building robust data pipelines that transform massive datasets into actionable reports for Finance, Tax, and Accounting stakeholders.

A key part of this role involves transitioning legacy reporting processes into a new, high-efficiency automation tool launching this month. You will act as a bridge between big data infrastructure and business-critical financial insights.

Key Responsibilities

• Data Transformation & Architecture: Design, implement, and support scalable ETL/ELT pipelines to extract data from various AWS internal services and transform it to meet specific Finance/Tax business needs.
• Big Data Management: Manage large-scale datasets within the Amazon Data Lake, ensuring high performance and data integrity for high-stakes financial reporting.
• Process Expedition: Analyze existing manual reporting workflows and "expedite" them through automation, reducing hours spent on manual "Internal Closes."
• Reporting & Visualization: Build and maintain sophisticated dashboards in Amazon QuickSight (and other internal BI tools) to provide real-time visibility into financial health.
• Tool Adoption & Migration: Play a lead role in the deployment of the team's new internal automation tool, migrating existing logic and ensuring a seamless launch.
• Stakeholder Collaboration: Partner with Finance and Accounting teams to translate complex tax/accounting requirements into technical data specifications.

Required Skills & Qualifications

Technical Core

• SQL Mastery: Expert-level SQL (Redshift, PostgreSQL, or Athena) for complex data manipulation and performance tuning.
• AWS Ecosystem: Proficiency with S3, Redshift, AWS Glue, and Lambda. Experience with EMR for big data processing is highly preferred.
• Programming: Strong proficiency in Python (preferred), Java, or Scala for ETL automation and data scripting.
• BI & Analytics: Hands-on experience building production-ready reports in Amazon QuickSight or similar (Tableau/PowerBI).

Domain Experience

• Financial Context: Previous experience supporting Finance, Tax, or Accounting domains. Understanding of "Financial Close" cycles is a significant plus.

Professional

• Level: 4-7 years of experience (Mid to Senior).
• Communication: Excellent verbal and written English, capable of explaining technical trade-offs to non-technical finance partners.

Preferred Qualifications

• Experience with Amazon-internal data tools and service-oriented architectures.
• Knowledge of non-relational databases (DynamoDB) and data governance/security best practices for sensitive financial data.