Data Engineer, Pricing and Promotions Science Data and Insights

Amazon; Vancouver; On-site; CAD 103,000 - 173,000; Full time

Job summary

A leading technology firm in Metro Vancouver seeks a Data Engineer to design and build scalable data processing systems using AWS technologies. The role requires 4+ years of experience in data engineering, expertise in Python, Scala, and AWS services. The ideal candidate will also mentor junior staff and drive data quality improvements. Salaries range from $103,300 to $172,600 annually, depending on experience.

Benefits

Medical benefits

Equity options

Flexible working hours

Qualifications

• Minimum 4 years of experience in data engineering.
• Experience with distributed systems and large data sets.
• Proficient in one modern scripting or programming language.

Responsibilities

• Design and operate scalable data processing systems.
• Develop custom data processing frameworks and automation tools.
• Optimize data pipeline performance and cost-efficiency.

Skills

Data extraction

Data processing

Collaboration

Mentoring

Big data technologies

Education

Master's degree in computer science or related field

Tools

AWS (Redshift, S3, Glue, EMR, Kinesis)

SQL

Airflow

Job description

Data Engineer, Pricing and Promotions Science Data and Insights

Are you passionate about developing the next generation of data infrastructure capable of handling complex, mission-critical data pipelines and analytics workloads? Do you want to build next generation data engineering solutions that leverage the latest AWS technologies to process a broad range of business and customer data?

Join our Pricing & Promotions Science, Data and Insights team, where you'll have the opportunity to continuously improve the systems that enable Amazon's annual worldwide revenue of billions of dollars.

Key job responsibilities

• Design, build, and operate highly scalable, fault‑tolerant data processing systems using modern AWS services like Redshift, S3, Glue, EMR, Kinesis, and Lambda, and orchestration systems using Airflow
• Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools
• Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions
• Continuously optimize data pipeline performance, reliability, and cost‑efficiency using best practices in CI/CD and infrastructure‑as‑code
• Mentor junior engineers and share your knowledge of data engineering best practices
• Stay up‑to‑date with the latest big data technologies and architectural patterns, and drive the adoption of innovative solutions

A day in the life

• Identify key areas of concerns/limitations with current architecture and build next‑generation frameworks and systems that enable data teams to deliver on future needs
• Build automated data quality monitoring, audit and reconciliation mechanisms
• Develop and maintain core infrastructure and services for multiple data engineering teams
• Improve efficiency of operations in terms of cost, effort and reliability

About the team

The Pricing and Promotions Science Data and Insights Org strives to accelerate Customer, Seller, and overall Amazon success through the proactive development of automated intelligent pricing and promotions science and analytics systems. We facilitate making trustworthy data‑driven decision making at scale. We look around corners for both long‑term and short‑term flywheel causal impacts, and think holistically, from sourcing to CX, and all customer journey touch points in between.

Basic Qualifications

• 4+ years of data engineering experience
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with SQL
• Experience with data audit and reconciliation strategies.
• Experience with data pipeline orchestration frameworks, such as Airflow.
• Experience with streaming data processing technologies.

Preferred Qualifications

• Experience with non‑relational databases / data stores (object storage, document or key‑value stores, graph databases, column‑family databases)
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

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 for this position ranges from $103,300/year up to $172,600/year. Salary is based on a number of factors and may vary depending on job‑related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign‑on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Applicants should apply via our internal or external career site.

Posted: June 23, 2025 (Updated 4 days ago)

Posted: June 5, 2025 (Updated 3 months ago)

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