Data Engineer, Alexa Smart Home

Amazon is hiring a Data Engineer, Alexa Smart Home in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
The posting mentions Bedrock, Replicate and SageMaker 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

Data engineer for Alexa Smart Home building data pipelines, analytics environments, and datasets prepared for AI model consumption.

BedrockReplicateSageMakerPythonScalaJavaSQL

prompt-engineeringfine-tuningdata-engineeringetldata-modelingsqlai-pipelines

The Alexa Smart Home Team is looking for a talented, highly motivated Data Engineer to join our Decision Sciences team. We provide actionable business insights that inform future products and services that will power the next generation of Alexa-enabled smart home devices. As a Data Engineer, you will work in one of the world's largest and most complex data-warehouse environments. You will work closely with Product Management, Software Development, Data Science, and other peer Data Engineering teams to develop scalable and innovative analytical solutions, process and store terabytes of low latency structured and unstructured data, and enable the Smart Home team to build successful, data driven strategies to provide the best customer experience. Data privacy is the top priority, and you will have the opportunity to design data infrastructure that delivers the best-in-class data privacy and compliance for retaining the customer trust.

You will be responsible for designing and implementing a data integration and analytical environment using various tools and using Python, Scala, or Java to automate the ETL, analytics, and data quality platform from the ground up. You will design and implement complex data models, model metadata, build reports and dashboards, and own data presentation and dashboarding tools for the end users of our data products and systems. You will write scalable, highly tuned SQL queries running over billions of rows of data and will develop data access platforms to drive adoption of data driven decision making across the Smart Home organization. Beyond traditional data engineering, you will leverage AI capabilities to enhance data pipeline development, transforming raw data into structured datasets ready for downstream AI model consumption, analytics use cases, and proactive data quality validations. This agility is critical at a moment when speed of AI adoption directly translates to business impact for our smart home customers.

You should have deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms. You should have excellent business and interpersonal skills to be able to work with business owners to understand data requirements, and to implement efficient and scalable ETL solutions. You should be an authority at crafting, implementing, and operating reliable, scalable, cost optimized solutions to replicate and transform data from production systems into offline datastores.

Key job responsibilities
• Work with the product and development teams within Alexa org to understand the product vision and requirements.
• Work with Product Managers, BI engineers, Software Engineers and Data Scientists to design, implement and support high quality data products.
• Partner with cross functional teams across Devices organization to ingest relevant datasets into the Alexa Smart Home BI data-warehouse.
• Collaborate with other peer data engineers to build self-service data platforms that possess key capabilities like data discovery, data lineage, proactive data monitoring and security/compliance monitoring.
• Manage data infrastructure, including capacity planning, cost optimization, and performance tuning.
• Leverage and manage AWS services like Bedrock, Sagemaker, S3, Redshift, Athena, Kinesis, Lambda, Data Lake etc.
• Implement data pipelines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
• Build data pipelines that support AI/ML use cases and enable integration with AWS AI services such as Amazon Bedrock and SageMaker to embed AI capabilities into production workflows.
• Collaborate with Data Scientists to adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
• Help continually improve ongoing data infrastructure processes, automating or simplifying self-service modeling and production support for stakeholders.

About the team
The Alexa Smart Home Decision Sciences team provides the data and analytical foundation that powers insights across our rapidly growing smart home ecosystem. We work with data from millions of connected devices, customer interactions, and partner integrations to help shape product strategy, improve customer experience, and drive business growth. We operate in a collaborative environment where innovation and customer obsession are at the core of everything we do.

Basic qualifications

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 4+ years of SQL experience

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with Apache Spark / Elastic Map Reduce
- Experience working with large language models (LLMs), including prompt engineering, model selection, and instructions fine-tuning to optimize model performance for analysis against large datasets
- Experience with scripting and API integration with AWS AI services such as Amazon Bedrock and SageMaker

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, Alexa Smart Home 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, Alexa Smart Home 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 May 19, 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

Prompt engineeringFine-tuningData EngineeringETLData ModelingSQLAI PipelinesBedrock

Also common in data engineer jobs at this level

Databricks Machine learning Azure Airflow Generative AI Snowflake

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

How do you structure and test a prompt to get consistent output from a language model?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
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 modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Prompt engineering, Fine-tuning, Data Engineering, ETL, and Data Modeling. 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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