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Data Engineer, Central InfraOps Analytics Team

Amazon
Posted a month ago, valid for 24 days
Location

Seattle, WA 98164, US

Salary

$101,300 - $160,000 per year

Contract type

Full Time

Health Insurance
Paid Time Off
Employee Assistance
Flexible Spending Account

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Sonic Summary

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  • The Data Engineer role at Amazon Web Services is focused on enabling data-driven decision-making within the Data Center Infrastructure Operations team.
  • Candidates are required to have at least 1 year of data engineering experience, along with skills in data modeling, warehousing, and building ETL pipelines.
  • The position offers a competitive salary range of $101,300 to $160,000 annually, depending on experience and qualifications.
  • Key responsibilities include designing and maintaining ETL pipelines, optimizing data storage, and collaborating with business stakeholders to translate their needs into data solutions.
  • The role emphasizes ownership of data solutions, requiring the engineer to monitor infrastructure health, develop automated processes, and ensure data integrity.
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.
Basic Qualifications: - 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell) Preferred Qualifications: - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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 - 101,300.00 - 160,000.00 USD annually
USA, WA, Seattle - 101,300.00 - 160,000.00 USD annually



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