Big Data Engineer - Seattle or Dallas, Worldwide Revenue Analytics

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Job summary
This role open in Seattle & Dallas. Relocation offered from within the US to any of these locations. Amazon is a hybrid work environment.

The AWS World Wide Revenue Operations (WWRO) Revenue technology team is responsible for publishing Daily Estimated Revenue (DER) and
monthly Amortized Sales Revenue (ASR). DER and ASR are used by downstream customers in AWS Finance, Accounting, Sales
Operations, Segmentation & Planning (S&P), Data & Analytics and Compensation to set quotas, manage sales goals, forecast,
and derive business insights. We collect and process billions of usage and billing transactions every single day and relate it to the largest data feed supported by Salesforce.com. We transform this raw data into actionable information in the Data Lake and make it available to our internal service owners to analyze their business and service our external customers.
We are truly leading the way to disrupt the big data industry. We are accomplishing this vision by bringing to bear Big Data technologies like Elastic Map Reduce (EMR) in addition to data warehouse technologies like Spectrum to build a data platform capable of scaling with the ever-increasing volume of data produced by AWS services.

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 interpersonal skills to be able 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 authority at crafting, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data lake. Above all, you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive growth.

BASIC QUALIFICATIONS

• Bachelor's Degree in Computer Science or a related technical field, and 5+ years of related employment experience.
• 5+ years of work experience with ETL, Data Modeling, and Data Architecture.
• Expert-level skills in writing and optimizing SQL.
• Experience with Big Data technologies such as Hive/Spark.
• Proficiency in one of the scripting languages - python, ruby, linux or similar.
• Experience operating very large data warehouses or data lakes.

PREFERRED QUALIFICATIONS

• Master's Degree in Computer Science or related field.
• Proficiency 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.
• Demonstrate 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.
• Meets/exceeds Amazon’s leadership principles requirements for this role
• Meets/exceeds Amazon’s functional/technical depth and complexity for this role.
• Experience with AWS services including S3, Redshift, EMR and RDS