Massachusetts Jobs

Description

We are seeking an experienced Data Engineer to join our Performance & Insights team at Amazon Robotics. The ideal candidate will have deep expertise in AWS technologies, including Redshift, Athena, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and SageMaker. You will play a key role in operationalizing statistical and ML models, collaborating with Data Scientists and Business Intelligence Engineers to deploy models using SageMaker Pipelines and Feature Store, ensuring scalability and near real-time insights. Your role will involve designing, developing, and maintaining scalable data pipelines and models that drive automation, reporting, and decision-making across multiple Robotics teams.

A successful candidate will have strong ETL experience, expertise in data warehousing, real-time data processing, and data lake architectures, and a track record of optimizing AWS-based infrastructure for cost efficiency and performance. Strong organizational skills, an ability to manage multiple projects, and experience in mentoring junior data engineers are highly valued in this role.

Key job responsibilities

• Design, build, and maintain scalable ETL pipelines and data warehouse solutions that support real-time and batch data processing.

• Partner with data scientists to productionize ML models, leveraging AWS services such as SageMaker, Lambda, and Step Functions for deployment.

• Lead efforts in near real-time analytics, working with streaming technologies like Kinesis, Kafka, and Flink.

• Optimize data workflows, query performance, and infrastructure costs within Redshift, Athena, and other AWS data services.

• Develop and maintain highly available and fault-tolerant data pipelines, ensuring data integrity, security, and compliance.

• Serve as the technical SME for automation, self-service analytics, and AWS data platform improvements.

About the team

The P&I team is dedicated to developing and scaling analytics products and services that provide deeper insights into the AR network's performance and its underlying causal factors. By leveraging advanced analytics, automation, and deep domain expertise, we drive efficiencies, mitigate risks, and ensure robust data integrity across all AR support functions. Our outcomes empower service and support teams across a global network of AR sites with predictive insights, proactive network monitoring, and comprehensive risk assessments—enabling an “Always Ready” support model. We develop core data pipelines and infrastructure solutions to enable supportability and ensure availability of data-driven insights to our customers.

Basic Qualifications

• 3+ years of data engineering experience

• Experience with data modeling, warehousing and building ETL pipelines

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

Preferred Qualifications

• Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets

• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

• Familiarity with deploying ML models in production (SageMaker Pipelines, Feature Store, batch inference).

• Experience with orchestration tools (e.g., Apache Airflow, Step Functions, Prefect).

• Hands-on experience in optimizing Redshift queries, tuning Spark jobs, and managing large-scale data pipelines.

• Proficiency in Python, Scala, or Java for data engineering and automation.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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.