Data Engineer, Ww Promotions Data and Insights

Amazon Amazon · Big Tech · CA, BC +1 · Data Science

Data Engineer role focused on building and operating scalable data processing systems using AWS technologies. The role involves data modeling, ETL pipeline development, and collaboration with data scientists and analysts. While not directly building AI models, the role will utilize generative AI tools to enhance workflow efficiency and identify opportunities for AI integration.

What you'd actually do

  1. 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
  2. Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools
  3. Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions
  4. Continuously optimize data pipeline performance, reliability, and cost-efficiency using best practices in CI/CD and infrastructure-as-code
  5. Mentor junior engineers and share your knowledge of data engineering best practices

Skills

Required

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Python
  • Scala

Nice to have

  • AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • generative AI tools
  • effective prompting
  • evaluation practices
  • recognize opportunities where generative AI could enhance products, workflows, or customer experiences

What the JD emphasized

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines