DESCRIPTION

Business Intelligence Engineer
We are looking to hire an insightful, results-oriented Senior Business Analyst to produce and drive analysis for the Security & Loss Prevention (SLP) function in Amazon. The mission of the SLP team is to mitigate security and operational risks to the associates, data, physical assets & inventory. The SLP team ensures smooth run of the day-to-day business operations by protecting against various threats and by managing security and loss prevention risks, thereby ensuring a safe and secure work environment. This is achieved by preventing the security related risks and vulnerabilities as early as possible; by intervening in unfolding incidents and exposures in order to minimize any negative impact; and by investigating thoroughly security related incidents in order to identify and remove root causes and to prevent re- occurrence.
About the organisation
Risk & Investigations for Network & Goods (RING)
RING is a global inventory and goods risk management program initiated in Global Security Organisaiton (GSO), to manage security and loss within Amazon to contribute towards Amazon’s profitability, and sustainability. RING engages in a wide variety of tech and non-tech initiatives to support customers and stakeholders get visibility on losses and take action to prevent the losses by strengthening all aspects of the Amazonian operational network.
Data Services within RING is a dedicated function focused on Data Services, Shrink Analytics and Products deployment enabling the charter of RING namely Shrink, Investigations and E2ESN. DSP will work with GSO teams to standardize and automate business processes and mechanisms to provide deep actionable insights to support field teams to conduct investigations, identify fraudulent MOs, build scalable programs and thus prevent loss. DSP aspires to be the business transformation platform of choice that reshapes the way our customers and stakeholders leverage technology to build and operate their businesses.
We are looking for a top analytical mind to leverage our unique data and big data technologies to drive actionable insights that helps our self-service advertisers reach their full potential.
An ideal candidate will be someone with sound technical background in managing large data infrastructures, working with petabyte-scale data, building scalable data solutions/automations and driving operational excellence. An ideal candidate will be someone who is a self-starter that can start with a Platform requirement & work backwards to conceive and devise best possible solution, a good communicator while driving customer interactions, a passionate learner of new technology when the need arises, a strong owner of every deliverable in the team, obsessed with customer delight, business impact and ‘gets work done’ in business time.
As a key analytics partner, the Business Intelligence Engineer will influence the direction of the business by leveraging our data to deliver insights that drive decisions and actions. This role involves translating broad business problems into specific analytics projects, conducting deep quantitative analyses, and communicating results effectively. We see a high potential for growth in this role as we transform our data into actionable insights to continue to fuel the growth of this business. The role will help the organization identify, evaluate, and evangelize new techniques and tools to continue to improve our ability to deliver value to RING Stakeholders.
This role requires an individual with excellent business, communication, and technical skills, enabling collaboration with various functions, including product managers, software engineers, data scientists, financial analysts, as well as senior leadership. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced and high-energy environment.
This role promises to give exposure to a high growth business that is taking off. This BIE will be actively involved in building new metrics, understanding impact of product changes, and identifying opportunities for growth through exploratory analyses including use of lightweight statistical techniques. This role provides the opportunity to use emerging technologies such as machine learning to build models and tools used by management for strategic decision making.

Key job responsibilities
• Design/implement automation and manage our massive Data infrastructure to scale for the Analytics needs of GSO
• Enable efficient data exploration, experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
• Build data pipelines to enable new metrics
• Complete project based deep dives to drive business insights and guide product strategy
• Present findings and recommendations to business leadership
• Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
• Drive operational excellence strongly within the team and build automations and mechanisms to reduce operations
• Enjoy working closely with your peers in a group of very smart and talented engineers.

BASIC QUALIFICATIONS
• 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipeline
• Experience writing complex SQL queries
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience to process data for modeling
PREFERRED QUALIFICATIONS
– Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
– Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

BASIC QUALIFICATIONS

– 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
– Experience with data visualization using Tableau, Quicksight, or similar tools
– Experience with data modeling, warehousing and building ETL pipelines
– Experience in Statistical Analysis packages such as R, SAS and Matlab
– Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

PREFERRED QUALIFICATIONS

– Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
– Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets