Sr. Support Engineer; Data & Analytics Operations (Cloud/Data Warehouse)

Canada Posted Jun 19, 2026 0 views

Compensation

Compensation not disclosed

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Job description

Team: IT

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Support Engineer; Data & Analytics Operations (Cloud/Data Warehouse) based in Canada.

This role sits at the core of a large-scale data and analytics environment, ensuring the stability, reliability, and performance of critical data platforms that support enterprise decision-making. You will act as a key operational expert responsible for maintaining end-to-end data pipelines, resolving complex production issues, and safeguarding data integrity across on-premise and cloud ecosystems. The position blends deep technical troubleshooting with operational leadership, requiring close collaboration with engineering, development, and business stakeholders. You will work in a fast-paced environment where incident response, continuous improvement, and system optimization are part of the daily rhythm. With exposure to both legacy systems and modern cloud-native architectures, the role offers a unique opportunity to bridge traditional data warehouse technologies with emerging cloud and AI-driven platforms. This is a 24/7 rotational support role designed for professionals who thrive in high-impact, mission-critical environments.

Accountabilities:

Provide advanced operational support for enterprise data warehouse and analytics platforms across on-premise and cloud environments.
Monitor, maintain, and ensure the stability of end-to-end data pipelines, batch jobs, and application performance.
Troubleshoot and resolve complex data issues, job failures, and system discrepancies using strong analytical and SQL-based investigation skills.
Support and enhance ETL processes using tools such as Informatica (PowerCenter and IDMC) and related data integration technologies.
Collaborate with development, DevOps, and business teams to ensure smooth production deployments and operational transitions.
Implement incident, problem, and change management processes while ensuring SLA adherence and compliance standards.
Deploy production enhancements using DevOps tools and CI/CD pipelines while maintaining system reliability.
Document technical processes, operational procedures, and system designs to ensure knowledge sharing and continuity.
Proactively identify opportunities for operational improvements and contribute to automation and optimization initiatives.
Act as a bridge between technical teams and stakeholders, ensuring clear communication of incidents, risks, and resolutions.
Mentor and support peers by sharing knowledge and contributing to a strong support engineering culture.

Requirements:

Bachelor’s degree or equivalent experience in Computer Science, Data Science, Engineering, or related technical field.
Minimum 4+ years of experience in Data Warehouse, Business Intelligence, or Data & Analytics operational support environments.
Strong expertise with ETL tools, particularly Informatica PowerCenter and/or Informatica IDMC.
Hands-on experience with SQL, relational databases (SQL Server, Oracle, DB2), and data processing workflows.
Familiarity with mainframe technologies (TSO, JCL, COBOL, ZEKE) and hybrid data environments is highly valued.
Working knowledge of Windows and Unix/Linux operating systems.
Exposure to BI tools such as SAP BusinessObjects (Universe Designer, Web Intelligence, Crystal Reports) is an asset.
Experience with DevOps tools (BitBucket, Jenkins, Ansible, CI/CD pipelines) is considered a strong advantage.
Cloud exposure (AWS or equivalent), including services like Glue, Lambda, Redshift, and Python/R, is a plus.
Strong problem-solving skills with the ability to analyze complex systems and resolve critical incidents under pressure.
Excellent communication skills and ability to collaborate across technical and business teams.
Ability to work in a 24/7 rotational support model, including occasional overtime.
Curiosity, adaptability, and a continuous learning mindset, especially regarding emerging technologies such as AI and cloud data platforms.

Benefits:

Competitive salary range with performance-based bonus opportunities.
Comprehensive retirement, pension, and savings programs.
Hybrid work model with flexibility for remote and in-office collaboration.
Flexible working hours aligned with operational requirements.
Strong focus on continuous learning, professional development, and upskilling.
Exposure to advanced data, cloud, and AI-driven technologies in a large-scale enterprise environment.
Inclusive, diverse, and collaborative workplace culture.
Participation in impactful projects that shape enterprise data strategy and operational excellence.

Comp not disclosed

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