SR. DATA ENGINEER, SALES INSIGHTS AND DATA SCIENCE
Amazon - Austin, TX
posted 3 months ago
About the position
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud, known as cloud computing. As a Senior Data Engineer within the SMGS Ops team, you will be immersed in a large, complex, and dynamic data environment. We are seeking an experienced Data Engineer who possesses a unique ability to integrate multiple heterogeneous data sources to create efficient, flexible, and scalable data warehouse and reporting solutions. The ideal candidate will have experience deploying analytics platforms to over 5000 users, optimizing architecture for performance and enhancing the end-user experience. You should be enthusiastic about learning new technologies and implementing solutions that empower internal customers and scale the platform. Your role will involve collaborating with Research Scientists and business owners across both technical and non-technical teams to develop and define key business questions, and subsequently build the solutions that address those questions. In this position, you will be the expert responsible for designing, implementing, and operating a stable, scalable, and low-cost environment that facilitates the flow of information from the data warehouse into end-user facing reporting applications such as Tableau or AWS QuickSight. Your primary focus will be on aggregating large datasets to answer business questions and drive data-driven decision-making. This role will also involve building the engineering infrastructure and data products for Startup (SUP) business teams, while collaborating with third-party data acquisition and SUP business development teams. Key responsibilities include planning, designing, implementing, and managing a deployment of a self-service data visualization platform, utilizing modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, and Hive. You will establish scalable, efficient, automated processes for large-scale data analysis and build data pipelines to support machine learning models for real-time and large-scale offline use cases. Additionally, you will support the development of performance dashboards that encompass key metrics for review with senior leadership and sales management, and work closely with business owners to create datasets that address their specific business inquiries. Furthermore, you will assist Sales Operations Leads and Analysts in analyzing usage data to derive new insights that fuel customer success.
Responsibilities
- Plan, design, implement, and manage a deployment of self-service data visualization platform (with front end as Tableau, QuickSight, and/or Apache Superset)
- Design, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.
- Utilize modern cloud database and storage concepts for data storage and versioning (Data Lakes with AWS S3)
- Establish scalable, efficient, automated processes for large scale data analysis
- Build data pipelines to feed machine learning models for real-time and large-scale offline use cases
- Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management
- Work with business owners and partners to build data sets that answer their specific business questions
- Support Sales Operations Leads, Analysts and beyond in analyzing usage data to derive new insights and fuel customer success
Requirements
- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
Nice-to-haves
- Experience with big data technologies such as Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
Benefits
- Comprehensive medical, financial, and other benefits
- Equity and sign-on payments as part of total compensation package
- Flexible working culture to support work-life balance
- Ongoing mentorship and career advancement resources
