Amazon is looking for a motivated individual with strong database, analytical skills and technology experience to join the Display Ads Finance team.
A day in the life
In this position the successful candidate will be responsible for partnering with Finance and Business leaders to expand and optimize data infrastructure that supports weekly, monthly, quarterly and annual for the Display Ads Finance group and our stakeholders.
About the hiring group
· The candidate should enjoy creating pipelines, analyzing data, recommending and implementing solutions to facilitate financial and metrics reporting.
· Plan, design, implement, and manage a deployment of self-service data platform & visualization in Quicksight
· Create and maintain ETL procedures and SQL queries to bring data in from data warehouse and alternate data sources
· Utilize database technologies, including Redshift, AWS EMR and Quicksight to design, develop, and evaluate analyses and highly innovative business intelligence tools and reporting
· Scripting language such as Python preferred
· Establish scalable, efficient, automated processes for large scale data analyses
· Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management
· Work with business owners and partners to build data sets that answer their specific business questions
· Support Financial Analysts, Sales Operations Leads and beyond in analyzing usage data to derive new insights and fuel customer success
· Owning the design, operations and improvements for the Organizations Datawarehouse infrastructure
· Maintain, improve and manage all ETL pipelines and clusters
· Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
· Define metrics and KPIs to measure success of strategic initiatives and report on their progress
· Develop relationships and processes with finance, sales, business operations, solution delivery team, partner, BD, and other cross-functional stakeholders
· Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
· Collaborate with data scientists, BIEs and BAs to deliver high quality data architecture and pipelines.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
· 5+ years of experience as a Data Engineer or in a similar role
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience in SQL
· Bachelor degree in Computer Science or related technical field
· 7+ years of professional experience in data analytics or business intelligence space
· 5+ years of experience working on ETL, data modeling, business intelligence architecture
· Advanced skills in data mining using SQL, ETL, data warehouse as well as Excel
· Proven experience with BI data tools such as Power BI, Tableau, Qlik, Quicksight
· Experience building self-service reporting solutions using business intelligence software (e.g., OBIEE, Tableau, Amazon Quicksight, etc.)
· Demonstrated experience with at least one relational database technology such as Redshift, Oracle, MySQL or MS SQL
· Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)
· Ability to complete projects timely, accurately and with strong attention to detail, with continuous communication of progress updates to stakeholders
· Advanced degree in Data Science, Engineering, Statistics, Computer Science, Mathematics or related quantitative field
· Experience with Amazon Redshift, QuickSight, S3
· Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
· Experience with statistical languages like R
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
· Experience with building multi-dimensional data models to serve as a foundation for future analyses
· Excellent verbal/written communication & data presentation skills, including experience communicating to both business and technical teams
· Demonstrated ability to work effectively across various internal organizations