Posted 19 days ago
Data Engineer
@ Keasis
Montréal, Quebec
Requirements summary:
- • Client Engagement: Act as the technical face of the team, gathering requirements, presenting data solutions, and managing stakeholder expectations.
- Required Skills & Qualifications
- • Experience: 5–7 years of professional experience in data engineering.
- • Client-Facing Skills: Proven experience in client-facing roles, with excellent verbal and written communication skills to articulate technical concepts to non-technical stakeholders.
- Preferred Qualifications
- • Experience working in an Agile/Scrum environment.
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-10-22
- First seen by our source
- 2026-11-10
- Source record updated
- 2026-11-10
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Keasis
Job Title: Data Engineer (Pyspark & Python)
Location: Montreal, QC (Hybrid)
Type: Contract
Job Overview:
We are seeking a skilled Senior Data Engineer with 5 to 7 years of experience specializing in Python and PySpark. In this role, you will design, build, and optimize robust data pipelines while serving as a primary technical point of contact for clients. The ideal candidate bridges the gap between complex data engineering and strategic client communication.
Key Responsibilities
• Data Pipeline Development: Design, develop, and maintain scalable data processing pipelines using Python and PySpark.
• Client Engagement: Act as the technical face of the team, gathering requirements, presenting data solutions, and managing stakeholder expectations.
• Optimization & Performance: Tune Spark jobs for optimal performance, troubleshooting bottlenecks in large-scale data environments.
• Collaboration: Partner with cross-functional teams, including data scientists, analysts, and project managers, to deliver business-critical data products.
Required Skills & Qualifications
• Experience: 5–7 years of professional experience in data engineering.
• Core Technical Skills: Strong proficiency in Python and hands-on expertise with PySpark (Spark SQL, DataFrames, RDDs).
• Client-Facing Skills: Proven experience in client-facing roles, with excellent verbal and written communication skills to articulate technical concepts to non-technical stakeholders.
• Data Ecosystems: Solid understanding of SQL, data warehousing concepts, and cloud data platforms (AWS, Azure, or GCP).
• Software Practices: Familiarity with Git, CI/CD pipelines, and writing clean, maintainable code.
Preferred Qualifications
• Experience working in an Agile/Scrum environment.
• Knowledge of orchestration tools like Apache Airflow.
Journal
Only you can see this. Kept on this device, and in your account when you sign in.