Data Engineer II, GENIE, Alexa Proactive - ML Engineering (MLE)

We are looking for a passionate, talented, and inventive Data Engineer to lead the development of industry-leading data solutions to support conversational technology with multimodal systems.

As a Data Engineer with the GENIE ML Engineering team, you will be responsible for leading the development of novel data solutions, data modeling techniques, and data pipelines to advance our data analysis and business reporting for Customer Telemetry and related model training/analysis for state of the art conversational multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology e.g., data pipelines that feed into solutions to deliver customer features. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI). You will have significant influence on our overall strategy by helping define data, enrichment, model optimizations and evaluation. You will drive the system architecture, and spearhead the best practices that enable a quality infrastructure.

As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments using the latest set of tools. You will help GENIE teams and senior leadership within Alexa Devices understand our customers by providing data and metrics that provide insight into user experience. Our team is responsible for AI model analysis and/or training as well as analytical reports and metrics that are viewed at the highest levels in the organization. We are also working on near-real-time analytics using the latest set of tools for data visualization and investing in Big Data technologies. You should have deep expertise in the design, creation, management, and business use of extremely large datasets, as well as data security and privacy standards and best practices.

Key job responsibilities

1. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using AWS services and internal BDT tools
2. Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, Redshift, and OLAP technologies to support research needs
3. Interface with researchers and business stakeholders, gathering requirements and support ad-hoc data access to large data sets
4. Build and deliver high quality data sets to support applied scientists and customer reporting needs
5. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
6. Become a subject matter expert on Alexa and Amazon data sources relevant to Alexa Proactive use cases, and assist stakeholders with understanding and visualizing data
7. Educate the team on best practices for upholding data security and data privacy standards
8. Knowledge/Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
9. Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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

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)
- Experience working on and delivering end to end projects independently

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