Data Engineer, Central InfraOps Analytics Team
Amazon Web Services•Published 1 days ago•First seen 1 days ago
As a Data Engineer you will enable data-driven decision making within the Amazon Web Services Data Center Infrastructure Operations organization. The Infrastructure Operations Team is responsible for planning, implementing, monitoring and continuously improving the global Amazon Data Center infrastructure. The team supports all aspects of the Data Center based organizations, including but not limited to : Safety, Security, maintenance, operations, logistics, engineering and equipment management.
Key job responsibilities
Design, develop, and maintain ETL pipelines to ingest data into the data warehouse and data lake
Create and optimize logical data models that drive physical design for the Infrastructure Operations organization
Implement data quality measures and ongoing monitoring to ensure data integrity
Build scalable, efficient, and maintainable data solutions that support business intelligence needs
Optimize data storage and query performance across various data platforms
Develop automated processes to replace manual data operations
Collaborate with business stakeholders to understand data and reporting requirements
Translate business questions into data solutions that drive decision-making
Mentor and develop peers in data engineering best practices
Participate in code reviews, design discussions, and team planning
Improve self-service access to data for business users
Enhance code quality and dependency management
Automate manual processes to increase efficiency
Identify and resolve root causes of complex data problems
A day in the life
At AWS, the Data Engineer fully embraces the "You Build It, You Own It" philosophy, taking complete ownership of data solutions from conception through deployment and ongoing maintenance. You design architectures, implement pipelines, and remain responsible for their health and evolution as business needs change.
Each day begins with reviewing pipeline alerts and data quality metrics, followed by a 15-30 minute team stand-up to align on priorities and discuss blockers. You'll spend time monitoring infrastructure, reviewing logs for ETL pipeline health and data lake performance, then dedicate time to address stakeholder queries and prioritizing incoming requests via email, Slack and intake forms. The majority of your time is spent developing and maintaining ETL pipelines that ingest infrastructure operational data from global data centers, which includes writing code, debugging issues, optimizing queries, and implementing quality checks. The role requires frequent context switching between developing new data models, supporting existing infrastructure, and consulting on data utilization.
Key challenges you'll tackle include unifying and understanding fragmented data from diverse data center systems, enabling infrastructure monitoring, supporting analytics for capacity planning, driving optimization through data insights, automating manual processes, creating self-service access for business users, maintaining quality across massive datasets, ensuring compliance with strict security requirements, designing for scale as AWS expands globally, and modernizing legacy systems to reduce technical debt.
About the team
Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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.
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, VA, Herndon - 132,100.00 - 178,800.00 USD annually
Key job responsibilities
Design, develop, and maintain ETL pipelines to ingest data into the data warehouse and data lake
Create and optimize logical data models that drive physical design for the Infrastructure Operations organization
Implement data quality measures and ongoing monitoring to ensure data integrity
Build scalable, efficient, and maintainable data solutions that support business intelligence needs
Optimize data storage and query performance across various data platforms
Develop automated processes to replace manual data operations
Collaborate with business stakeholders to understand data and reporting requirements
Translate business questions into data solutions that drive decision-making
Mentor and develop peers in data engineering best practices
Participate in code reviews, design discussions, and team planning
Improve self-service access to data for business users
Enhance code quality and dependency management
Automate manual processes to increase efficiency
Identify and resolve root causes of complex data problems
A day in the life
At AWS, the Data Engineer fully embraces the "You Build It, You Own It" philosophy, taking complete ownership of data solutions from conception through deployment and ongoing maintenance. You design architectures, implement pipelines, and remain responsible for their health and evolution as business needs change.
Each day begins with reviewing pipeline alerts and data quality metrics, followed by a 15-30 minute team stand-up to align on priorities and discuss blockers. You'll spend time monitoring infrastructure, reviewing logs for ETL pipeline health and data lake performance, then dedicate time to address stakeholder queries and prioritizing incoming requests via email, Slack and intake forms. The majority of your time is spent developing and maintaining ETL pipelines that ingest infrastructure operational data from global data centers, which includes writing code, debugging issues, optimizing queries, and implementing quality checks. The role requires frequent context switching between developing new data models, supporting existing infrastructure, and consulting on data utilization.
Key challenges you'll tackle include unifying and understanding fragmented data from diverse data center systems, enabling infrastructure monitoring, supporting analytics for capacity planning, driving optimization through data insights, automating manual processes, creating self-service access for business users, maintaining quality across massive datasets, ensuring compliance with strict security requirements, designing for scale as AWS expands globally, and modernizing legacy systems to reduce technical debt.
About the team
Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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.
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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.
Basic Qualifications
- 3+ years of data engineering experience
- 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Preferred Qualifications
- 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)
- Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
- Experience working on and delivering end to end projects independently
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Herndon - 132,100.00 - 178,800.00 USD annually