Data Engineer I, DSP Analytics

Amazon is hiring a Data Engineer I, DSP Analytics in Hyderabad, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
The posting mentions Python, SQL and AWS among its tools and skills.
Level classes it as a mid-level role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design and build data infrastructure supporting GenAI applications and develop data ops automation agents.

PythonSQLAWSGenerative AI

ai-researchdata-engineeringetldata-pipelinesmachine-learningdata-operations

Do you enjoy diving deep into data, developing real-time and batch pipelines that generate actionable insights?
The DSP Analytics team has an exciting opportunity for a Data Engineer to make impactful contributions to Amazon's Delivery Service Partner (DSP) program tackling modern data challenges by combining traditional engineering practices with transformative analytics and Generative AI.

You'll help design and build the next generation of data infrastructure powering GenAI applications, and develop agents that automate the end-to-end data operations lifecycle. We are a team of Data Engineers working closely with Data Scientists, Economists, and Analysts turning machine learning and AI research into scalable products that delight customers worldwide.

You're passionate about technology, strongly biased toward going deep to find insights, and driven to build scalable analytical platforms. You're relentless about quality and reliability, and comfortable communicating across different levels of leadership. If that sounds like you, we'd love to talk.

Key job responsibilities
• Design, build, and maintain robust data pipelines to acquire, process, and store data from various sources such as databases, APIs, and external data providers.
• Develop and optimize ETL (Extract, Transform, Load) processes to clean, enrich, and structure raw data into a usable format for analysis and reporting.
• Implement and manage data warehousing solutions to ensure efficient data storage, retrieval, and query performance.
• Establish data quality standards, perform data validation, and proactively identify and address data quality issues.
• Optimize data pipelines and storage solutions to handle large volumes of data while maintaining high performance and reliability.
• Ensure data privacy and security by implementing access controls, encryption, and compliance with data protection regulations.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide the necessary data infrastructure to support their needs.
• Maintain comprehensive documentation for data pipelines, data models, and processes to facilitate knowledge sharing and troubleshooting.
• Implement monitoring solutions to proactively detect and address data pipeline failures or performance bottlenecks.
• Keep abreast of industry trends and emerging technologies in data engineering to recommend and implement improvements to our data infrastructure.

About the team
We are the Amazon DSP Analytics team, supporting all business pillars across the DSP organization horizontally, with the vision to enable data-, insights-, and science-driven decision-making. We are an exceptionally talented and fun-loving team. Here, you'll have the opportunity to dive deep into complex business and data problems, drive large-scale technical solutions, and raise the bar for operational excellence. We love sharing ideas and learning from each other, and we believe in using those ideas to disrupt the status quo.

Basic qualifications

- 1+ years of data engineering experience
- Experience with SQL
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
- Knowledge of database, data warehouse, or data lake solutions

Preferred qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value

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, DSP Analytics 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer I, DSP Analytics is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IN, TS, Hyderabad.
The job was posted on September 17, 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

AI ResearchData EngineeringETLData PipelinesMachine learningData OperationsPythonSQL

Also common in data engineer jobs at this level

Databricks Azure Airflow Snowflake Java Google Cloud

Pay

Typical data engineer job: $147k

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 research question you investigated. What did you find?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl 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?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Research, Data Engineering, ETL, Data Pipelines, and Machine learning. 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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