Senior Business Intelligence Engineer, Data Solutions & Engineering, Security

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Job summary
Do you want to build a security platform that provides a data-driven experience for Amazon engineers and raises the security bar for Amazon customers? At Amazon, security is our highest priority and the our Vulnerability Management (AVM) team is responsible for defining and driving large software security initiatives across Amazon. We are looking for an engineer that will automate all business metrics, analyze all aspects of our business, and provide recommendations that directly affect Amazon vulnerability management priorities.


About Us
Our organization is accountable for the end-to-end software vulnerability lifecycle across all aspects of Amazon. We are responsible for building the platform that monitors intelligence, detects vulnerabilities, drives remediation response, and drives innovation to meet the scale and demand of all Amazon customers. Working with teams such as EC2, S3, RDS, CloudHSM, Containers, and Amazon Linux requires us to dive deep into all aspects of first- and third-party software across Amazon including Operating Systems, firmware, databases, service/system hardening, cryptography, and audit analysis. We are passionate about diving in at any depth to identify and build solutions that keep our customers safe.

About You
We expect that you are as passionate about finding and prioritizing areas of improvement that keep our customers safe as we are. As the subject matter expert, you own the automation of the authoritative datasets that facilitate business analysis and track business performance. You have a track record of using those datasets and insights to work directly with business and product teams to drive change within your business. You can work directly with business owners and program managers to translate ambiguous situations into technical implementations that deliver business recommendations that exceed the expectation of your business partners.

You understand that automation is key to your success and constantly find techniques to ensure automation and derived datasets are a feature of all your data activities. However, you recognize that there is a balance between the construction of new insights versus delivering automation for others to construct new insights. Delivering tools that your team can use to perform analysis and replicate findings, allows you to scale business analysis to subject matter experts and expedites your ability to continuously deliver automated metrics and insights. We want you because you have a relentlessly high bar when solving hard data-driven problems at scale and relish the opportunity to challenge the norm.

About the team
Inclusive Team Culture

Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• Bachelor’s Degree in Engineering, Mathematics, or related field, or equivalent professional experience
• 6+ years of relevant work experience in ETL, data science, business analytics, or comparable experience
• Led the delivery of at least one automated data solution that met customer expectations
• Led the delivery and operational support of at least one automated data solution on a cloud platform
• Computer Science fundamentals in data structures
• Computer Science fundamentals in algorithm design, problem solving, and complexity analysis
• Proficient with data warehouse best practices and terminology
• Proficient with at least one modern programming language, such as C, C++, C#, Java, Python, Rust, or Go
• Proficient at drawing insights from data and communicating analyses that affect business prioritization.
• Self-driven leader that delivers with minimal project definition and incomplete or dirty data

PREFERRED QUALIFICATIONS

• MBA or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or equivalent professional experience
• Experience influencing software engineering, data processing, and data security best practices
• Experience taking the lead to coordinate multiple technical teams to deliver on your behalf to get the data required to inform stakeholders and affect business strategy
• Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience delivering a system that delivers an integrated experience across real-time and batch insights
• Experience conducting data analysis that cannot be conducted on a single host
• Experience using AWS technologies such as EC2, S3, Redshift, EMR, Glue, Athena, and SageMaker
• Meets/exceeds Amazon’s functional/technical depth and complexity for this role