Data Engineer - Snowflake
Company shown to members 🔒 · Remote · Canada only
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First recorded by Psst: 14 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- 12+ years required
- Where you can live
- Canada only
- Skills and tools
- sql, python, aws, machine learning
- Job type
- Full-time
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Job details
- Where you can work
- Canada
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- 12+ years required
- Employer publication date
- 17 March 2026
- First recorded by Psst
- 14 October 2026
- Last checked at the source
- 10 November 2026
About the job
The company the company is a fast-growing advanced the company consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted the company partner for several Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best the company global consulting team in the world.
The Data Engineer will be responsible for architecting, designing, and implementing advanced the company capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data the company to the next level.
Requirements
- 12+ years of overall industry experience specifically in data engineering with a heavy focus on the AWS Cloud stack and AI.
- 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
- Advanced proficiency in Python, SQL, and PySpark.
- Creating and optimizing complex data processing and data transformation pipelines using python
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Deep experience with Snowflake/Databricks on AWS, dbt, and distributed computing frameworks like Apache Spark.
- Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
- Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
The company the company provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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