Data Engineer II, Alexa Audio
- Vancouver, BC, Canada
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Job details
- Posting language
- English
- Posted
Original job description
As a Data Engineer, you'll drive the development of data pipelines and automation to process massive datasets for our next-generation Audio features powered by advanced AI technologies. You'll work closely with cross-functional teams, including product management, design, engineering, Business Intelligence, and data science. You'll also lead the integration of these advanced AI systems into Alexa Audio's core capabilities, ensuring a seamless and intuitive customer experience.
Key job responsibilities
Key job responsibilities
- Work closely with data scientists, BI, and engineers to create robust data architectures and pipelines
- Develop and manage scalable data pipelines to extract, transform, and load data from various sources
- Collaborate with stakeholders to understand business requirements and translate them into data-driven solutions
- Automate data processing and reporting workflows to improve efficiency and data integrity
- Implement data quality checks and monitor processes to maintain high data accuracy
- Simplify and enhance the accessibility, clarity, and usability of large and complex datasets through the development of data cubes and data sharing solutions
- Develop and manage scalable, automated, and fault-tolerant data solutions using technologies such as Spark, EMR, Python, Redshift, Glue, and S3
About the team
Our team consists of Business Intelligence Engineers (BIEs), Data Engineers (DEs), Data Scientists (DS’s) and DS/BI Managers, who bring deep experience in both business analytics and data science. We cover the data needs of Music, Radio, Podcasts, Books, News and Generative audio. Basic Qualifications: - 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 3+ years of SQL (Structured Query Language) experience 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)
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. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, BC, Vancouver - 103,300.00 - 172,600.00 CAD annually
More about this job
Responsibilities
You will develop and manage scalable data pipelines and robust architectures to process massive datasets for Alexa Audio features. Additionally, you will collaborate with cross-functional teams to automate workflows and ensure high data integrity and accessibility.
Requirements
Candidates must have at least 3 years of experience in data engineering, data modeling, and building ETL pipelines. Proficiency in SQL is required, and experience with AWS technologies is preferred.
Skills
- Data engineering
- Data modeling
- Data warehousing
- ETL pipelines
- SQL
- Spark
- EMR
- Python
- Redshift
- AWS Glue
- S3
- Data architecture
- Automation
- Data quality
- Data cubes
- Business intelligence
Benefits
- Health insurance
- Medical insurance
- Dental insurance
- Vision insurance
- Prescription insurance
- Basic life insurance
- AD&D insurance
- Deferred profit sharing plan
- Paid time off
- Restricted stock units
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Software
- Technology
- Engineering
Keywords
- Data engineering
- Alexa
- Big data
- AI
- Data pipelines
- Automation
- Data modeling
- Data warehousing
- ETL
- SQL
- Spark
- EMR
- Python
- Redshift
- AWS Glue
- S3
- Kinesis
- FireHose
- Lambda
- IAM
- Business intelligence
- Data science
- Data architecture
- Data integrity
- Data cubes
- Generative audio
- Cloud computing
- Non-relational databases
- Object storage
- Graph databases