Job Description
Business Data Technologies (BDT) makes it easier for teams across Amazon to produce, store, catalog, secure, move, and analyze data at massive scale. Our managed solutions combine standard AWS tooling, open-source products, and custom services to free teams from worrying about the complexities of operating at Amazon scale. This lets BDT customers move beyond the engineering and operational burden associated with managing and scaling platforms, and instead focus on scaling the value they can glean from their data, both for their customers and their teams. We own the one of the biggest (largest) data lakes for Amazon where 1000's of Amazon teams can search, share, and store EB (Exabytes) of data in a secure and seamless way; using our solutions, teams around the world can schedule/process millions of workloads on a daily basis. We provide enterprise solutions that focus on compliance, security, integrity, and cost efficiency of operating and managing EBs of Amazon data.
Key job responsibilities
CORE RESPONSIBILITIES: · Be hands-on with ETL to build data pipelines to support automated reporting · Interface with other technology teams to extract, transform, and load data from a wide variety of data sources · Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, Redshift. · Model data and metadata for ad-hoc and pre-built reporting · Interface with business customers, gathering requirements and delivering complete reporting solutions · Build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark. · Build and deliver high quality data sets to support business analyst, data scientists, and customer reporting needs. · Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers · Participate in strategic & tactical planning discussions
A day in the life
As a Data Engineer, you will be working with cross-functional partners from Science, Product, SDEs, Operations and leadership to translate raw data into actionable insights for stakeholders, empowering them to make data-driven decisions. Some of the key activities include: Crafting the Data Flow: Design and build data pipelines, the backbone of our data ecosystem. Ensure the integrity of the data journey by implementing robust data quality checks and monitoring processes. Architect for Insights: Translate complex business requirements into efficient data models that optimize data analysis and reporting. Automate data processing tasks to streamline workflows and improve efficiency. Become a data detective! ensuring data availability and performance
Numbers & Facts
| Location | Seattle, WA |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://Amazon.com/militaryroles |
About Company
At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
Skills
- Amazon Web Services (AWS)unmatched
- Analysis Skillsunmatched
- Best Practicesunmatched
- Business Analysisunmatched
- Business Supportunmatched
- Cross-Functionalunmatched
- Customer Relationsunmatched
- Customer Support/Serviceunmatched
- Customer/Client Researchunmatched
- Data Analysisunmatched
- Data Managementunmatched
- Data Modelingunmatched
- Data Processingunmatched
- Data Qualityunmatched
- Data Scienceunmatched
- Data Setsunmatched
- Data Structuresunmatched
- Database Extract Transform and Load (ETL)unmatched
- Ecosystemsunmatched
- Leadershipunmatched
- Machine Toolunmatched
- Metadataunmatched
- Open Sourceunmatched
- Python Programming/Scripting Languageunmatched
- Quality Monitoringunmatched
- SQL (Structured Query Language)unmatched
- Scalable System Developmentunmatched
- Strategic Planningunmatched
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