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Data Engineer II (Level 5), Alexa Devices, Sales & Marketing

Amazon, Seattle

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Data Engineer II (Level 5), Alexa Devices, Sales & Marketing

Job ID: 2888509 | Amazon.com Services LLC

Love science and data? So do we! The Alexa Devices, Sales & Marketing organization is looking for an experienced Data Engineer to deliver solutions that help deepen our understanding of customers. You will be joining the Alexa Marketing Science (AMS) team, whose mission is to surface timely, scientifically-grounded insights about customers to guide marketing and product leaders.

The ideal candidate has excellent technical skills, analytical abilities, written and verbal communication skills, and the ability to influence cross-functional teams. They are an expert with SQL, ETL, Tableau (or similar data visualization tools) and have an ability to quickly translate business requirements into technical solutions. The candidate is a self-starter and team player and able to think big while paying careful attention to detail.

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. We help marketing and product teams in Alexa Devices understand our customers by providing data and metrics that provide insight into user experience. Our team is responsible for mission critical research and 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.

The role offers a unique opportunity to manage and build new data storage, pipelining, and visualization solutions from the ground up. You should possess high attention to detail, have excellent communication skills, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred. Above all you should be passionate about working with large data sets and someone who loves to bring datasets together to answer business questions and drive change.

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 research 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 marketing researchers’ use cases, and assist non-technical stakeholders with understanding and visualizing data
  7. Educate the team on best practices for upholding data security and data privacy standards
  8. Maintain clear and consistent documentation of relevant data sources and code frameworks

BASIC QUALIFICATIONS

  • 3+ 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

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)

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.

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