Data Engineer - Remote / Telecommute

Cynet Systems Inc; Toronto; Remote; CAD 90,000 - 130,000; Full time

Job summary

Cynet Systems Inc is seeking a skilled Data Engineer in Toronto to own core data pipelines while ensuring data quality and optimal performance. The role involves collaborating with teams, designing robust data models, and writing maintainable code, contributing to the overall data engineering roadmap.

Qualifications

• 3+ years of professional experience in data engineering.
• Proficiency in SQL and designing data models.
• Experience with ETL tools in Spark or similar technologies.

Responsibilities

• Manage core data pipelines, ensuring performance and data quality.
• Collaborate with stakeholders to align data solutions with business goals.
• Write clean and maintainable code for data processing.

Skills

Data validation

Data visualization

SQL

Data modeling

Collaboration

Python

Java

ETL

Workflow management

Job description

Job Description:

Responsibilities:

• Take ownership of core data pipelines, ensuring resilience, optimal performance, timely delivery, data quality, and seamless onboarding of new features.
• Continuously evolve data models and schemas to meet business and engineering requirements Implement and maintain systems to monitor and enhance data quality and consistency.
• Develop tools that support self-service management of data pipelines (ETL) and perform SQL tuning to optimize data processing performance.
• Contribute to the Data Engineering team’s technical roadmap, ensuring alignment with team and stakeholder goals.
• Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency Conduct code reviews to uphold code quality standards and facilitate knowledge sharing.
• Participate in on-call rotations to maintain high availability and reliability of workflows and data pipelines.
• Collaborate with internal and external partners to remove blockers, provide support, and achieve results.

Requirements:

• 3+ years of professional experience in data engineering.
• Experience working directly with cross-functional stakeholders from analytics, science, product and engineering to align data solutions with business goals.
• Proficiency in validation, explanation and visualization to present and analyze data and insights.
• Strong skill in designing complex data model and resilient data pipelines that enrich them.
• Proficiency in SQL being able to understand complex business logic and implement own one.
• Deep understanding of MPP systems and hands-on experience with ETL in Spark or similar technologies.
• Proficiency in writing data transformation scripting in Python, Java or similar.
• Hands-on/Practicalexperience with workflow management tools (e.g., Airflow or similar).
• Proven ability to collaborate with cross-functional stakeholders (analytics, science, product, and engineering) to ensure data solutions align with business objectives.
• Proficient in data validation, explanation, and visualization for effective data analysis and insight presentation.