Data Engineer, Amazon Smart Vehicles

Summary: Amazon is a leading company in technology and innovation, and they are seeking a Data Engineer for their Smart Vehicles team. The role involves building data pipelines and production-grade datasets that support product decisions and enhance automotive experiences. Responsibilities: - Build and maintain data pipelines that deliver reliable, analysis-ready and prompt-ready datasets from diverse sources using SQL, Python, and AWS technologies - Design canonical tables and metrics that product, science, and leadership teams depend on - Navigate complex data infrastructure to find the right sources and make informed modeling decisions - Ensure data quality and pipeline reliability through proactive validation, monitoring, and upstream collaboration - Write clear documentation that enables stakeholders to self-serve - Work directly with product managers, scientists, and engineers to turn data questions into reliable answers, with enough business context to know what matters and why - Find opportunities to automate repetitive work and raise the bar on how the team builds and delivers data - Contribute to the team's technical direction by evaluating new tools, frameworks, and approaches Required Qualifications: - 1+ years of data engineering experience - Experience with SQL - Experience with data modeling, warehousing and building ETL pipelines - Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets - Experience scripting for automation (e.g., Python, Perl, Ruby) - Bachelor's degree in a relevant field or equivalent work experience Preferred Qualifications: - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with data transformation - Experience with AWS Tools and Technologies (Redshift, S3, EC2) - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience with database, data warehouse or data lake solutions - Experience working directly with business stakeholders to translate between data and business needs - Experience with workflow orchestration tools such as Airflow, Step Functions, or similar frameworks - Experience with data quality testing or observability frameworks - Exposure to privacy-aware data collaboration or governed analytics environments - Familiarity with infrastructure-as-code tools such as CDK, Terraform, or CloudFormation Required Skills: Data Engineering, SQL, ETL Pipelines, AWS Technologies Important Skills: Data Modeling, Data Transformation, Data Visualization, Automation Scripting, Data Quality Testing, Workflow Orchestration Nice-to-Have Skills: Infrastructure-as-Code, Soft Skills Benefits: Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, Paid time off, Parental leave