Data Engineering Analyst

Role Overview

Delivery Responsibilities

• Work with data, design, product, and executive stakeholders on data-related technical issues.
• Use programming, ETL tools, and data virtualization to manage integration tools, databases, warehouses, and analytical systems.
• Build data transformation processes, data structures, metadata, dependency management, and workload management.
• Design infrastructure for extracting, transforming, and loading structured, unstructured, and big data.
• Prepare data for predictive and prescriptive modeling and assist with analytics and machine learning deployments.
• Develop scalable data pipelines and API integrations and build analytics tools for business performance insights.
• Improve data models that feed business intelligence tools and increase data accessibility.
• Implement data quality frameworks and test the reliability and performance of the data ecosystem.
• Lead projects and follow DevOps procedures through delivery and operations.

Operations and Improvement

• Coordinate remediation of data issues and support stakeholders in managing data throughout its lifecycle.
• Manage data access and disposal requests and ensure data availability requirements are met.
• Monitor data protection controls, identify gaps, and recommend solutions with Security, Privacy, and Risk Management teams.
• Automate manual processes, optimize data delivery, and redesign infrastructure for scalability.
• Monitor the performance and stability of the centralized data ecosystem.
• Develop KPIs and conduct an annual Data Architectural Maturity assessment.
• Provide education and mentoring on data engineering practices and processes.
• Analyze data engineering trends and align techniques with industry best practices.

Leadership

• Communicate with peers across Servus to support data maturity and organizational alignment.
• Lead by example, take ownership of work items, and drive operations to completion.
• Participate in data prioritization and stakeholder meetings and communicate decisions to teams.
• Conduct internal audits to measure adherence to established standards.

Experience and Education

• Bachelor's degree or diploma in Computer Science, Engineering, Information Systems, or a related field.
• At least 4 years of experience in data engineering management, Python or Java, SQL, and data modeling.
• Experience with Agile methods and machine learning tools.
• Strong understanding of data science.
• A Data Engineering certificate is an asset.

Other Role Requirements

• Excellent written, verbal, presentation, communication, and teamwork skills.
• Ability to lead teams, train others, and work independently.
• Strong project, organizational, and time management skills.
• Skills in documentation, facilitation, negotiation, and stakeholder influence.
• Ability to solve complex problems and meet deadlines under pressure.
• The work arrangement is Remote First, with occasional travel potentially required.

Benefits

• The employer describes competitive compensation with performance-based incentive pay and profit sharing.
• Benefits include health and wellness, vacation, retirement savings, training and development, flexible work options, and career advancement opportunities.
• Employees can participate in volunteer activities and receive credit union member benefits.