Sr. Support Engineer; Data & Analytics Operations (Cloud/Data Warehouse) in Canada Creek, Nova Scotia at Jobgether
Explore Related Opportunities
Job Description
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.
- 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.
- 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.
- 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.