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As a Senior Data Engineer on this team, you will drive efficiency in data handling processes, setup product analytics, drive advanced analysis and build new metrics which are key inputs to improve the health, scale and growth of the Private Pricing Program. You will work collaboratively with the business leaders (including the VP of Private Pricing), operations, and engineering teams on many non-standard and unique business problems and support business initiatives by collecting required and related data from external/internal sources.Key job responsibilities
• Owning the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using AWS services and internal tools
• Build and deliver high quality data sets to support data scientists and customer reporting needs.
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
• Translate basic business problem statements into analysis requirements.
• Use analytical and statistical rigor to answer business questions and drive business decisions.
• Find and create ways to measure the customer experience to drive business outcomes.
• Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
• Write queries and output efficiently, and have in-depth knowledge of the available in area of expertise. Pull the needed with standard query syntax; periodically identify more advanced methods of query optimization. Convert to make it analysis-ready.
• Recognize and adopt best practices in reporting and analysis: integrity, design, analysis, validation, and documentation.
• Troubleshoot operational quality issues.
• Review and audit existing jobs and queries.
• Recommending improvements to back-end sources for increased accuracy and simplicity.About the team
Diverse Experiences:
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth:
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance:
- 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
- Bachelors Degree in relevant Technical Field
- Experience operating large data warehouses
- Experience developing, deploying, and managing production data pipelines in AWS
- Experience deploying and managing machine learning models deployed into productionPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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