Data Engineering Analyst

Role Overview

Delivery

• Assist stakeholders with data-related technical issues and requirements.
• Use programming, ETL tools, and data virtualization solutions to manage integrations, databases, warehouses, and analytical systems.
• Build data transformation processes, data structures, metadata, dependencies, workload management, and scalable pipelines.
• Design infrastructure for extracting, transforming, and loading structured, unstructured, and big data sources.
• Prepare data for predictive and prescriptive modeling and assist with machine learning and analytics deployments.
• Develop API integrations, analytics tools, data models, data integrations, and data quality frameworks.
• Monitor data quality, ecosystem reliability, performance, and production data availability.
• Lead projects, contribute to backlogs, document architecture, and follow DevOps procedures.

Operations and Improvement

• Coordinate remediation of data issues and support data management throughout the data lifecycle.
• Manage data access and disposal requests and provide guidance on data availability requirements.
• Monitor data protection controls and collaborate with Security, Privacy, and Risk Management teams.
• Automate manual processes, improve scalability, monitor the data ecosystem, and assess data architectural maturity.
• Educate and mentor business and IS staff on data engineering practices and processes.
• Analyze data engineering trends and align techniques with organizational information needs.

Leadership

• Communicate with peers and stakeholders across Servus to support data maturity and organizational alignment.
• Lead by example, take ownership of work items, and drive operations to completion.
• Participate in prioritization and stakeholder meetings and conduct internal audits against established standards.

Experience and Education

• Bachelor's degree or diploma in Computer Science, Engineering, Information Systems, or a related field.
• 4+ years of experience in data engineering, Python or Java, SQL, and data modeling.
• Experience with Agile methods and machine learning tools.
• Strong understanding of data science.
• Strong communication, teamwork, project management, documentation, facilitation, and negotiation skills.
• Experience leading teams and training others, with the ability to work independently.
• A Data Engineering certificate is an asset.

Work Arrangement

• The work arrangement is remote first.
• Occasional travel to Edmonton, Calgary, or Red Deer may be necessary.

Benefits

• Benefits include health and wellness coverage, vacation, retirement savings, performance-based incentive pay, profit sharing, training, career advancement, and flexible work options.