Data Engineer I, Worldwide Operations Finance, WW Ops Finance S&A, WW Ops Finance S&A

Amazon is hiring a Data Engineer I, Worldwide Operations Finance, WW Ops Finance S&A, WW Ops Finance S&A in Bengaluru, India. Level rates it ; you can apply on Level.

AI in this role

Build scalable data pipelines and AI-powered dashboards to support operations finance analytics and cost-performance tracking.

pythonsqlsparkawss3glueredshiftairflowemrlambda

etldata-engineeringai-dashboardsdata-pipelines

Are you excited about turning complex financial data into trusted, actionable insights that help Amazon operate more efficiently across the globe? The Worldwide Operations Finance team is looking for a Business Intelligence Engineer I to help build and scale a unified data platform that supports over 100 active finance users across 11 countries. In this role, you will build scalable data pipelines, create AI-powered dashboards, and deliver curated datasets that drive cost-performance tracking, weekly business reviews, and monthly book closures. You will work at the intersection of operations and finance analytics, replacing legacy regional data stores with consolidated, standardized datasets that tracks 500+ operational and cost metrics at daily granularity. This is a great time to join: the team is revamping the legacy datasets , dashboards and processes and is actively migrating to a new AWS-based infrastructure, giving you hands-on experience working on migrating to CI/CD deployed pipelines, while expanding coverage to new markets.

Key job responsibilities
* Design, build, and maintain scalable ETL pipelines and data solutions using Python, SQL, Spark, and AWS services (S3, Glue, Redshift, Airflow, EMR, Lambda)
* Optimize query performance and resource usage across the data platform, participate in code reviews and design discussions, and identify process improvements that increase automation and reduce manual effort
* Document solutions thoroughly to ensure maintainability, validate outputs against source data and business logic, and handle data in accordance with Amazon policies
* Develop AI-powered dashboards and intelligent agents that automate metrics bridging, commentary generation, and deep-dive queries, enabling finance users to make faster data-driven decisions
Collaborate with finance stakeholders, data engineers, and product teams to gather requirements, integrate data feeds from multiple sources, and ensure datasets are accurate, accessible, and aligned with evolving business needs

A day in the life
You start your morning reviewing pipeline health dashboards and triaging data quality alerts on cost data flowing across supply chain legs. By mid-morning, you are collaborating with finance analysts to reconcile discrepancies between finance, stores, and operations datasets. After lunch, you work with product teams and finance partners to define cost estimation logic for newly launched business lines, warehouse types, and carrier nodes, ensuring the allocation approach is consistent across markets. You then build and test the ETL pipeline to support it. You wrap up the day with a design session on upcoming datasets, ETL pipelines, dashboards or conduct code reviews to make sure that our solution scales across all regions.

About the team
Our team within Operations Finance builds and operates the unified data platform that powers financial reporting, bridging, and analytics for over 100 finance customers across all Rest of World (RoW) countries. We support 10+ data producer teams and are focused on scaling automation, improving data quality, and incorporating AI-driven workflows for both our builders and our customers. If you want to shape how a global finance organization interacts with data, this is the place to do it.

Basic qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
- Experience with one or more scripting language (e.g., Python, KornShell)
- Require 3+ years of creating production quality data pipelines along and exposure to data modelling

Preferred qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Master's degree

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Data Engineer I, Worldwide Operations Finance, WW Ops Finance S&A, WW Ops Finance S&A at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Data Engineer I, Worldwide Operations Finance, WW Ops Finance S&A, WW Ops Finance S&A is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IN, KA, Bengaluru.
The job was posted on October 9, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ETLData EngineeringAI DashboardsData PipelinesPythonSQLSparkAWS

Also common in data engineer jobs at this level

Machine learning Azure Databricks Generative AI Snowflake Google Cloud

Pay

Typical data engineer job: $146k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where ai dashboards was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Walk me through how you've used Python in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ETL, Data Engineering, AI Dashboards, Data Pipelines, and Python. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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