Data Engineer, Central InfraOps Analytics Team

Amazon.com, Inc.
Herndon, United States of America
1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior
Compensation
$ 160K

Job location

Herndon, United States of America

Tech stack

Query Performance
Amazon Web Services (AWS)
Data analysis
Big Data
Software Quality
Code Review
Data Centers
Data Definition Language
Information Engineering
Data Integrity
ETL
Data Systems
Data Warehousing
Query Languages
IBM InfoSphere DataStage
Software Debugging
Decision Support Systems
Hadoop
Hive
Python
Korn Shell
Logical Data Models
MultiDimensional EXpressions
Operational Data Store
DataOps
Scala
PL-SQL
SQL Databases
SQL Server Integration Services
Usage Analysis
Scripting (Bash/Python/Go/Ruby)
Data Storage Technologies
Spark
Technical Debt
Electronic Medical Records
Data Lake
Data Management
Physical Design
Software Coding
Legacy Systems

Job description

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., 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.

Requirements

Do you have experience in Software coding?, * 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.

Benefits & conditions

3.53.5 out of 5 stars Herndon, VA $101,300 - $160,000 a year - Full-time, Pulled from the full job description

  • AD&D insurance
  • Parental leave
  • Health insurance
  • 401(k) matching
  • Paid time off
  • Vision insurance
  • Dental insurance, 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

Apply for this position