Data Engineer II, Alexa eXperience Data (AXD)

Job summary
The Alexa eXperience Data (AXD) is redefining itself to focus on the manufacturing the delivery of data products focused on driving customer experience (CX) insights.

These insights serve as inputs into the P&L, helps the organization understand accuracy of our AI algorithms, and users propensity to spend additional dollars based on their interactions.

The 3 year vision for this team is become a producer of comprehensive and complete Alexa specific customer interactions. Product Managers, Business Intelligence Engineers, Data Engineers, and Project Managers can then use it to understand how their features are being consumed. For example, How many users who have linked music account spend speaking to Alexa?, How many people ask for weather versus the news?

We are truly leading the way to disrupt the data warehouse industry. We are accomplishing this vision by leveraging relational database technologies like Redshift along with emerging Big Data technologies like Elastic Map Reduce (EMR) to build a data platform capable of scaling with the ever-increasing volume of data produced by AWS services. The successful candidate will can shape and build data lake and supporting data products for years to come.

You should have deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms. You should have excellent business and communication skills to work with business owners to understand data requirements, and to build ETL to ingest the data into the data lake. You should be an expert at designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data lake. Above all, be passionate about working with vast data sets and someone who loves to bring datasets together to answer business questions and drive growth.

Basic Qualifications

· 3+ years of experience as a Data Engineer or in a similar role
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience in SQL

Preferred Qualifications

· Expertise in ETL optimization, designing, coding, and tuning big data processes using Apache Spark or similar technologies.
· Experience with building data pipelines and applications to stream and process datasets at low latencies.
· Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
· Sound knowledge of distributed systems and data architecture (lambda)- design and implement batch and stream data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level data structures.
· Knowledge of Engineering and Operational Excellence using standard methodologies.


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