Big Data Engineer

- 4+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience with SQL
- 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 with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Experience with data audit and reconciliation strategies.
- Experience with data pipeline orchestration frameworks, such as Airflow.
- Experience with streaming data processing technologies.

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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.

The base salary for this position ranges from $103,300/year up to $172,600/year. Salary is based on a number of factors 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. Applicants should apply via our internal or external career site.
Are you passionate about data and code? Does the prospect of dealing with mission-critical data excite you? Do you want to build data engineering solutions that process a broad range of business and customer data? Do you want to continuously improve the systems that enable annual worldwide revenue of billions of dollars?

WW Promotions owns the entire promotions lifecycle running on Amazon marketplace, including sourcing, validation, merchandising and execution. We own critical pieces of technical infrastructure powering various promotion types, such as Deals, Coupons, BuyXGetY, Price Discounts, Sales Discounts etc. We are a highly innovative global organization revolutionizing the Selling Partner and Amazon Customer experience of running and engaging with promotions on a daily basis and during major promotional events such as Prime Day, Prime Big Deals Day, and Black Friday/Cyber Monday. Promotions are a critical component of Amazon’s flywheel that delights customers with high quality discounts across millions of products, and they place trust in the value offered by the promotion.

Our vision is simple - we want to run the best promotions in the industry. Through technology, we seek to constantly increase the quality of promotions - by identifying the best set of products to promote from the millions we carry; best promotion type that meets our business objectives and learning from the performance of our past promotions.

Key job responsibilities
We are looking for a well rounded Data Engineer with strong technical expertise, and someone who is passionate about data, and the insights that large amounts of data sets can provide. You should possess both a data engineering background and a business acumen that enables you to think strategically. You will experience a wide range of problem solving situations requiring extensive use of data collection and analysis. The successful candidate will work closely with Software Engineers, BI Engineers, Data scientists, Product Managers and other stakeholders across various organizations to drive major initiatives forward.


A day in the life
You will:
- Develop and enhance current data models and pipelines to support emerging business needs.
- Develop next generation architecture to support near real time analytics and operational use cases.
- Drive continuous improvements to data quality, compliance, processing times, cost and SLAs for existing pipelines
- Collaborate with Data Scientists, ML Engineers to develop machine learning features that feed into our next generation Forecasting and ML Models.
- Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with ever-growing data volumes and emerging use cases