You recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. You write high quality code to retrieve and analyze data as well as analyze and solve business problems at their root, stepping back to understand the broader context. Developing pragmatic analyses and choosing applicable solutions that add value to your business area, you understand data resources and know how, when, and which to use (and which not to use). By recognizing and using advanced analytical techniques to solve business problems, you develop analyses (whether fully formed or exploratory) for the business' sake, not for analyses' sake. You seek to understand the business objectives relevant to your area and align your work to those objectives and seek to deliver business value.
You will own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. within SQL, Redshift, Quicksights, etc. You will be required to design and influence operational best practices for reporting and analytics to enable the team to scale as we expand. You will empower data-driven decision making through implementing principles of data mining, data modeling, and analytical skills to define and measure critical metrics.
Key job responsibilities
- Design, implement and support an analytical data infrastructure
- Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis
- Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
BASIC QUALIFICATIONS
- Bachelor's degree
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience with data modeling, warehousing and building ETL pipelines
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)
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
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, PA, Pittsburgh - 132,100.00 - 178,800.00 USD annually
USA, TX, Dallas - 132,100.00 - 178,800.00 USD annually
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually
