Senior Data Engineer, GFP Analytics

Found in: Talent US C2 - 2 weeks ago


Austin, United States Amazon.com Services LLC Full time
The GFP Analytics Data & Infrastructure team consists of experienced engineers and manages a suite of core data services that ingests and processes all data related to Amazon’s rapidly growing delivery fleet of vans, trucks, electric vehicles, and more. The tech stack designed, built, and operated by the team uses an event-driven architectural paradigm enabled through creative use of AWS- and Amazon-internal data services.

As a senior data engineer on this team, you will have the exciting opportunity to work on one of the largest vehicle based data sets in the world. You will work closely with program managers, engineers, analysts and business teams to design solutions for their respective needs, which will require creativity and strong problem solving skills. You will also help in developing data engineering roadmaps that help build platforms to solve complex problems in efficient and scalable ways. This role will work backwards from customer problems to design solutions to meet the goals.

Additionally, you will be responsible for designing, developing, and operating a data service platform using Python, Airflow, and SQL to build the various ETL, analytics, and data quality components. You’ll automate deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS Cloud Formation. You will design and implement complex data models and build the end-to-end infrastructure for reports and dashboards to be created by our customers. You will work with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more.

This role may be located out of Austin (preferably), Nashville, Seattle, or Arlington.

Responsibilities include:
- Work with external data partners to establish SFTP connections to ingest various datasets
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using different AWS products such as Lambda, Glue, EMR, Kinesis Firehose
- Maintain and enhance existing data pipelines
- Create extensible designs and easy to maintain solutions with the long term vision in mind
- Interface with cross functional teams, gathering requirements and delivering data solutions
- Improve tools, processes, scale existing solutions, create new solutions as required based on team and stakeholder needs

About the team
Here at Global Fleet and Products (GFP), we are building the safest, most efficient, and most sustainable fleet in the world. GFP Analytics is a growing and dynamic team dedicated to the curation, governance, and analytics/reporting of data about our worldwide fleet of delivery vehicles, especially data related to managing the supply chain and ongoing operation of the fleet. We have two sub-teams, Data/Infra and BI/Analytics, comprised of a diverse set of product/program managers, data engineers, business analysts, and business intelligence engineers. We love data and helping our customers drive the GFP mission

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Bellevue, WA, USA | Nashville, TN, USA

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
- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience building data products incrementally and integrating and managing data sets from multiple sources
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience providing technical leadership on high-impact cross-fucntional technical project
- Experience with MPP databases such as Amazon Redshift

PREFERRED QUALIFICATIONS

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
- Proficiency in the DevOps style of software deployment (infrastructure-as-code)
- Proficiency with AWS database/ETL tools including Lambda, Glue, Redshift, DynamoDB
- Proficiency with AWS technologies including SNS, SQS, SES, Route 53, Cloudwatch, VPC
- Background in Big Data, non-relational databases, Machine Learning and Data Mining is a plus



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