Sr. Data Engineer, Benefits Experience and Technology (BXT)

The Benefits eXperience & Technology (BXT) team's mission is to make it easy for employees and their family to discover and use the benefits that apply to them.

Today’s traditional benefit experiences rely heavily on content, explanations, and instructions for people to understand what’s available to them and how to use it.

We are bringing personalized and friction-free benefits to the tip of the fingers of over five million people (our employees and their dependents).

Amazon Benefits help them live richer and fuller lives, be it by helping them in a moment of medical need, saving for retirement, or helping them with a vacation.

We are building a delightful mobile and web experience integrated with internal and external systems, so employees don’t have to go through hoops to get what they want.

We are breaking new ground with this level of experience and personalization.

We are looking for a Senior Data Engineer to support the BXT team in building efficient, flexible, extensible, and scalable ETA and reporting solutions.

You should be an expert with data lake fundamentals around storage, compute, etc., familiar with multiple data processing stacks like Spark, EMR, and core data concepts (e.

g. Data Modeling and Reporting). You should have deep understanding of the architecture for enterprise level data lake / mesh solutions using AWS stack or other cloud stacks.

You should have expertise in the design, creation, management, and business use of large data-sets. The candidate is expected to be able to build efficient, flexible, extensible, and scalable ETL and reporting solutions.

You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform.

Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics.

This role requires a pragmatic problem solver comfortable with ambiguity, with deep expertise in building and maintaining the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems.

A candidate will need to leverage a wide range of skills and best practices including an emphasis on data collection, storage, processing and reporting at scale for customer-facing applications and business reporting.

Additionally, we are seeking candidates with determination and rigor in engineering, deep curiosity and interest for applied sciences, creativity, and sound logic and reasoning.

In summary, this is an exciting opportunity to work with a dynamic team and make a significant impact on the business. The successful candidate will have strong business acumen, experience in developing reporting and analytical infrastructures, effective communication skills, and the ability to work effectively with cross-functional teams in a fast-paced environment and highly ambiguous work space.

Key job responsibilities

• Interface with Product Managers, Data / Applied Scientists, Software Engineers and Program Managers to determine requirements for data pipeline, storage, processing and reporting.
• Build scalable and production-ready data pipelines to extract features from petabytes of raw data.
• Manage data refreshes and perform systematic quality data checks at scale.
• Create metrics reports and dashboards to support business reporting, metrics deep dive, customer behavior analysis and feature engineering for ML applications.
• Design data sharing strategy, define data schema and develop tools to enable more efficient data sharing with partner teams which adhere to highly confidential and PII data handling guidelines.
• Serve as a tech lead of data engineering and manage cross-functional data related initiatives and collaborations.
• Recognizing and adopting best practices in reporting and analysis : data integrity, test design, analysis, validation, and documentation.
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

BASIC QUALIFICATIONS

• 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

PREFERRED QUALIFICATIONS

• Experience with big data technologies such as : Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses
• Experience working with benefits systems, insurance / payor systems, and / or healthcare IT systems
30+ days ago