Data Engineer II, Alexa AI - ML Engineering

Join Alexa AI - ML Engineering and help power personalized, proactive experiences for hundreds of millions of Alexa customers worldwide. As a Data Engineer II, you will design and own the large-scale data pipelines that turn raw customer-interaction signals into the context and features our personalization and proactive-agent models depend on, working side-by-side with SDEs to shape our data strategy and architecture.

• You will build and operate ETL/ELT pipelines processing billions of records a day, using AWS big-data services (Glue, EMR, Kinesis, Redshift, DynamoDB) and distributed compute.
• You will partner with SDEs and applied scientists to define data strategy, contracts, and feature pipelines, and to decide architecture direction together.
• You will own operational health: data migrations, schema/platform updates, and triage of pipeline tickets, directly supporting the SDE team's work.
• This is a high-visibility role: the data you deliver, and keep running, directly shapes what Alexa proactively tells customers, and when.

Key job responsibilities

• Partner closely with SDEs to help define data strategy, architecture direction, and the long-term roadmap for the team's data platform.
• Design, build, and own ETL/ELT pipelines that ingest, transform, and load customer-interaction and context data at a scale of billions of records per day.
• Own operational items end-to-end: data migrations, schema and platform updates, and triage/resolution of data-pipeline tickets, providing day-to-day support to the SDE team.
• Partner with applied scientists and ML engineers to define data contracts, feature pipelines, and data-quality checks feeding personalization and proactive-agent models.
• Operate and continuously improve production pipelines: optimize data delivery, redesign for scalability, manage deployments, and drive root-cause fixes for pipeline incidents.
• Establish and document best practices for data modeling, warehousing, and pipeline design across the team.

A day in the life

You'll join SDEs in a design discussion to shape data strategy and architecture, then pick up a migration or platform-update ticket and see it through to resolution. You'll trace a data-quality issue in a personalization feature pipeline, support SDEs with any operational asks on your pipelines, and monitor the health of systems processing billions of daily customer-interaction events. You'll partner with applied scientists to onboard new signal sources and triage pipeline alerts.

About the team

Alexa AI - ML Engineering builds the personalization and proactive-intelligence systems that let Alexa anticipate what customers need before they ask. Data Engineers work side-by-side with SDEs and applied scientists, combining data strategy and large-scale engineering to turn billions of daily customer-interaction signals into the context, features, and content that drive Alexa's ranking, personalization, and proactive-agent experiences. We value ownership, data quality, and working backwards from the customer. Basic qualifications

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

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)

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