Amazon Web Services (AWS), World-Wide Public Sector Reporting and Analytics team is seeking a Data Engineer with broad technical skills to help build the infrastructure and tools required to support our Global Sales & Operations Organizations.
In this role, the ideal candidate will be responsible for developing and managing big data systems using advanced data engineering knowledge in the data warehousing space and redefining best practices with a cloud-based approach to scalability and automation. Additionally, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines for production level systems. In partnership with machine learning engineers, business intelligence engineers and analysts, you will work backwards from our business questions to build reliable and scalable data solutions to meet the business needs. Finally, this individual will work closely with project management teams to ensure proper guidance, use cases, and documentation is available to our Sales and Operations teams.
Key job responsibilities
Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations.
Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.
Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
Implementing data structures using best practices in data modeling to provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.
Evaluating and making decisions around dataset implementations designed and proposed by peer data engineers. Mentor junior data engineers.
Manage AWS resources including EC2, Redshift, S3, etc. Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
Participating in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance to produce comprehensive, usable dataset documentation and metadata.
BASIC QUALIFICATIONS
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Herndon - 132,100.00 - 178,800.00 USD annually
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually
