- 3+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
- Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
- Proficiency in at least one modern programming language such as Python, Perl, Ruby, or Java.
- Knowledge of data management fundamentals and data storage principles
- Experience using big data technologies (Hadoop, Hive, Spark, EMR, etc.)
- Experience using business intelligence reporting tools such as Tableau, Quick Sight, or Cognos
Are you interested in building high-performance and globally scalable reporting and analytics infrastructure for product and program development efforts centered on AWS technologies? Global Learning and Development (GLD) is hiring a Data Engineer to lead the development of data solutions to enable insight generation for our flagship initiatives. GLD is responsible for the learning infrastructure at Amazon, comprised of both vendor and in-house tech. You will be a member of the GLD Data Science and Machine Learning Team, and help build and drive the data solutions and infrastructure needed for our product and program development.
As a Data Engineer (DE) in GLD, you will be responsible for designing and implementing scalable ETL processes in the AWS platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. You will act as the business-facing subject matter expert for data storage and feature instrumentation, with the responsibility of managing end-to-end execution and delivery across various work streams. You will help drive data architecture across many large datasets, perform exploratory data analysis, implement new data pipelines that feed into or from critical data systems at Amazon.
This position requires a passionate, solution-oriented candidate to lead the implementation of the analytical data infrastructure that will guide the decision making behind initiatives such as onboarding content optimization, success measurement and downstream impact analysis within the Global Learning and Development (GLD) domain. In addition, the candidate must have the ability to work with stakeholder groups to solve business problems and recommend data engineering solutions that are organized and simple to understand.
- 2+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst or Systems Analyst in a company with large, complex data sources
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations