Senior Python Data Platform Engineer

Compunnel, Inc.; Montreal; On-site; CAD 90,000 - 130,000; Full time

Job summary

A leading company is seeking a Senior Python Data Platform Engineer to join their C3 Data Warehouse team in Montreal. The position focuses on building a next-generation data platform for Technology Risk functions, collaborating with various teams to establish best practices in data pipelines and analytics. Applicants should have significant experience in Python, SQL, data pipeline development, and tools like Airflow and Snowflake.

Qualifications

• 10+ years in complex data environments with large volumes.
• 7+ years of hands-on SQL/PLSQL experience.
• Strong problem-solving and analytical skills.

Responsibilities

• Develop components in Python for a unified data pipeline framework.
• Establish best practices for Airflow, DBT, and Snowflake usage.
• Provide QA and UAT support by resolving potential data issues.

Skills

Python

SQL

Data Pipeline Development

Airflow

Snowflake

Spark

ETL Development

Education

Bachelor’s degree in Computer Science

Tools

Airflow

DBT

Snowflake

Job description

Client is seeking a Senior Python Data Platform Engineer to join the C3 Data Warehouse team. The role focuses on developing the next-generation centralized data platform that supports reporting and analytics solutions for Technology Risk functions across the firm. This position involves building a unified data pipeline framework in Python and integrating it with internal platforms for data quality, cataloging, discovery, logging, and metrics. The engineer will collaborate with data warehousing leads, analysts, ETL developers, infrastructure engineers, and data analytics teams.

Job Responsibilities:

• Develop components in Python for a unified data pipeline framework.
• Establish best practices for Airflow, DBT, and Snowflake usage.
• Assist in testing and deployment of data pipeline framework using CI/CD tools.
• Monitor and optimize data loads and query performance.
• Provide QA and UAT support by identifying and resolving potential data issues.

Required Skills:

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related field.
• 10+ years of experience in complex data environments with large volumes.
• 7+ years of hands-on SQL/PLSQL experience, writing complex queries.
• 7+ years of experience developing data pipelines and data warehouse solutions in Python (Pandas, NumPy, PySpark).
• 3+ years in hybrid data environments (on-prem and cloud).
• 3+ years of experience building Airflow DAGs (branching, dynamic DAG/task generation, error handling).
• Experience with structured, semi-structured, and unstructured data integrations (RDBMS, NoSQL, document DBs, etc.).
• Proficiency in Snowflake, Apache Spark, and Airflow (or Dagster).

Preferred Skills:

• Hands-on experience with DBT.
• Expertise in performance tuning for SQL queries, Spark jobs, and stored procedures.
• Understanding of E-R modeling (conceptual, logical, physical).
• Knowledge of advanced warehouse concepts (Factless Fact Tables, Temporal/Bi-Temporal models).
• Strong analytical and business requirement interpretation skills.
• Excellent verbal and written communication skills.
• Ability to manage concurrent priorities and work independently.
• Strong problem-solving skills and ability to resolve competing priorities.

Certifications:

[Optional – e.g., Snowflake, Python, or Cloud certifications preferred]

Education:

Bachelor’s degree required (Computer Science or related field)