Lead the development and implementation of advanced data engineering solutions to support the deployment and optimization of Generative AI models
Responsible for architectural design and planning, advanced data pipelines, model integration and optimization
Build and maintain data engineering solutions on cloud platforms using hyperscaler services
Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications
Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems
Understanding of indexing and vectorization to use with Generative AI prompt engineering
Strong understanding of fundamental data science concepts in NLP

Requirements

Bachelor's degree in computer science, data engineering, or a related field with 5+ years experience (Master's preferred)
Proven experience in data engineering, MLOps, ETL, and database management, QL and data manipulation languages
Azure, Python, Java, or Scala
data warehousing platforms (e.g., Databricks, Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark)
highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringMLOpsETLdatabase managementdata manipulation languagesPythonJavaScaladata warehousingbig data technologies

Certifications

Bachelor's degreeMaster's degree