Description

　　The Maintenance Automation Platform (MAP) team within the Global Reliability and Maintenance Engineering (RME) Central Team is looking for an exceptional Data Engineer to join us. If you are passionate about building highly scalable systems and tackling big data challenges, then this opportunity is for you!

　　Our primary mission is to provide a centralized high-quality data storage and access platform, empowering Global RME users to make data-driven decisions.

　　We are seeking a Data Engineer with a proven track record of delivering distributed data systems on AWS infrastructure. Your responsibilities will include system design, development, code reviews, peer mentoring, release processes, and system monitoring. The data engineering team collaborates with other engineers, product managers, and data science teams to create new data-driven capabilities, delivering process automation and performance optimization. A successful candidate will be a self-starter, comfortable with ambiguity, possess excellent attention to detail, and have the ability to thrive in a fast-paced and ever-changing environment, working effectively with cross-functional teams.

　　The ideal candidate thrives on working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. This role requires an individual with excellent data modeling, data architecture, and software development skills. The candidate should be an expert in building advanced data pipelines and innovative data solutions, passionately partnering with business stakeholders to identify strategic opportunities where improvements in data infrastructure can have a significant business impact. This individual is a self-starter, comfortable dealing with ambiguity, able to think big (while paying careful attention to detail), and enjoys working in a fast-paced and global team.

　　Key job responsibilities

　　Develop and design scalable and efficient data architectures on AWS. Ensure data architecture aligns with business goals and industry best practices.

　　Create and maintain robust data pipelines for ingesting, processing, and transforming data using AWS services such as Amazon Lake Formation, Glue, S3, Lambda, EMR, Kinesis, Elasticsearch, ECS

　　Experience with Infrastructure as Code, (such as CDK, CloudFormation or similar)

　　Design and implement data models to support analytical and reporting requirements. Optimize data structures for performance, scalability, and cost-effectiveness.

　　Optimize queries and performance for large-scale data processing using Redshift or other data warehousing solutions

　　Implement and enforce data security measures, including encryption and access controls. Ensure compliance with data privacy regulations and industry standards.

　　Set up monitoring and alerting for data pipelines and systems using AWS CloudWatch and other monitoring tools. Continuously optimize data processing workflows for performance and cost-effectiveness.

　　Develop and implement data quality checks to ensure the accuracy and reliability of data. Establish and enforce data quality standards and best practices.

　　Collaboration with Cross-functional Teams that included Data scientists, Research scientists, and Business Intelligence Engineers to understand data needs and deliver solutions.

　　We are open to hiring candidates to work out of one of the following locations:

　　Bellevue, WA, USA

　　Basic Qualifications

　　3+ years of data engineering experience

　　Experience with data modeling, warehousing and building ETL pipelines

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

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

　　Experience working on and delivering end to end projects independently

　　Preferred Qualifications

　　Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

　　Experience building large-scale, high-throughput, 24x7 data systems

　　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

　　Experience providing technical leadership and mentoring other engineers for best practices on data engineering

　　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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $105,700/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.