Data Engineer, AppStar Data Analytics & Engineering
Role details
Job location
Tech stack
Job description
Are you passionate about building data infrastructure that powers security insights and analytics at scale? Do you want to contribute to the modernization of a security data platform that enables measurable improvements in application security across Amazon?
As a Data Engineer on the AppStar DNA team (Data & Analytics Engineering), you will build and maintain data pipelines and infrastructure that support the AppStar organization. You will work across multiple data domains to develop the data infrastructure that powers analytics and reporting.
You should be a builder who is passionate about data engineering and eager to learn. You thrive in solving technical problems, building reliable data pipelines, and contributing to a high-performing team. You bring solid expertise in data modeling, ETL/ELT pipeline design, and distributed data systems, and you're excited to grow your skills in modern data architectures and AWS technologies., * Design and implement ETL/ELT pipelines using SQL, Python, and AWS services (Redshift, Glue, S3, Lambda, Step Functions, Athena, Apache Airflow)
- Build and maintain data models, conformed dimensions, and entity models that support downstream consumption
- Contribute to the migration and modernization of legacy security data pipelines to modern lakehouse patterns (Apache Iceberg, Spectrum, Lake Formation)
- Ensure data quality, lineage, and freshness in data pipelines
- Follow data engineering best practices: data modeling standards, naming conventions, data quality frameworks, CI/CD for data pipelines, and operational excellence
- Identify and resolve data pipeline issues-simplify complex data flows, remove bottlenecks, and address technical debt
- Collaborate with senior engineers, business intelligence engineers, data scientists, and security stakeholders to deliver scalable data solutions
- Design, implement, and support platforms providing secured access to large datasets
- Analyze and solve problems at their root, stepping back to understand the broader context
- Learn and understand a broad range of Amazon's security data resources and know when, how, and which to use
- Continually improve data infrastructure and pipelines, automating or simplifying self-service support for datasets
- Participate in design reviews, on-call rotations, and incident response for production data pipelines
About the team Why Amazon Security At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
AppStar DNA Team (Data & Analytics Engineering) The AppStar DNA team supports the AppStar organization, which is responsible for securing applications at Amazon. Our team is committed to building world-class data infrastructure that provides the foundation for analytics solutions, enabling visibility into security performance and driving data-informed decision-making across security teams. We work with massive volumes of security data to deliver the infrastructure that powers insights with immediate influence on how Amazon secures its applications and protects customer trust.
Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Inclusive Team Culture In Amazon Security, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training and 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, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Requirements
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
- Experience with data modeling, warehousing and building ETL pipelines, * 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)
Benefits & conditions
AD&D insurance, Parental leave, Health insurance, 401(k) matching, Paid time off, Vision insurance, Dental insurance, Flexible spending account