Data Engineering Analyst

About the opportunity

Join Servus Credit Union - Canada’s Largest Credit Union! We are hiring for a Data Engineering Analyst in our Data Technology & Infrastructure department. This role is Remote First. Posting Closes: September 18, 2026 For Internal Use Only: P2/C At Servus Credit Union, we do things differently—because we’re a credit union, not a bank. And that difference matters. We believe in putting people before profits, which is why our members are also our owners. Every dollar we earn is reinvested into the things that matter most: our members, our employees, and our communities. Whether it’s through profit sharing, competitive rates, or local initiatives that make a real impact, we’re here to help Albertans feel good about their money. We’re looking for passionate, values-driven people to join our team. We welcome individuals from all backgrounds who are aligned with our values and are eager to contribute in meaningful ways. If you're excited to grow your career with a team that’s innovative, hardworking, collaborative and deeply rooted in community, we want to meet you. Join Servus and discover a better way to work. The Intermediate Data Engineering Analyst is responsible for working closely with the IS Architecture team to expand and optimize our Data Warehouse architecture, as well as optimize the collection, the flows and distributed access of data. The Intermediate Data Engineering Analyst designs and builds data pipelines and is an experienced data wrangler. This role supports our software developers, data analysts, database administrators and data scientists on data initiatives. The Intermediate Data Engineering Analyst works to ensure optimal data delivery architecture remains consistent throughout ongoing projects. The Intermediate Data Engineering Analyst must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. This role is instrumental and contributes to the optimization our data architecture to support our next generation of products and services for our members. What You'll Be Doing Delivery Working with stakeholders including data, design, product, and executive teams and assisting them with data-related technical issues. Uses programming skills, ETL tools and data virtualization solution to develop, customize and manage integration tools, databases, warehouses, and analytical systems. Builds processes supporting data transformation, data structures, metadata, dependency, and workload management. Design and build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using structure and unstructured data as well as big data sources. Create data tools for analytics and data scientist team members that assist them in building and optimizing our products for growth targets and other strategic objectives. Prepare data for predictive and prescriptive modeling. Assist in the deployment of analytics programs, machine learning and predictive models. Assembling large, complex sets of data that meet non-functional and functional business requirements. Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics. Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization. Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Contributes to engineering and architectural documentation. Tests the reliability and performance of each part of a data ecosystem. Design and build data integrations and data quality framework. Works closely with all business units and engineering teams to develop strategy for long term data platform architecture. Lead projects and their delivery to ensure projects are completed as planned and exceed/meet defined expectations. Follow DevOps procedures throughout the delivery and operations. Contribute to the work items in the backlog(s) and communicate on delivery progress. Operations Work with various stakeholders within the organization to understand the impacts of their data issues and recommend & coordinate remediation activities. Support business stakeholders in ensuring data is managed throughout its lifecycle. Manage data access requests, data disposal requests, etc. and provide guidance to the stakeholders to ensure necessary steps and taken. Ensure data availability requirements are being met. Take ownership of subsequent improvement tasks. Monitor data protection controls identify gaps and recommend solutions in collaboration with Security, Privacy and Risk Management groups Continuous Improvement Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability. Monitoring the overall performance and stability of the centralized data ecosystem. Develop KPIs and conduct a Data Architectural Maturity assessment on an annual basis. Assist in providing education and mentoring to business and IS staff on data engineering practices and processes to increase awareness and adoption. Assist with identification and implementation of changes for data and IS continuous improvements. Assist in preparation of business cases and alignment with other strategic initiatives. Analyze data engineering trends to ensure alignment with industry best practices and continuously improve associated techniques within Servus to meet its information needs. Leadership Contribute to Servus culture and data maturity needs though effective communications with peers within other areas across Servus. Motivate the team with leading and be respectful in communications, lead by example. Ensure alignment with strategy and direction set by the leadership and demonstrate willingness to commit to a direction and drive operations to completion. Take accountabilities of work items and demonstrate proactiveness in data engineering activities and operations. Demonstrated ability to manage adversity and challenging situations. Conduct internal audits to measure and assure adherence to established standards. Participate in Data Prioritization meetings and other stakeholder meetings and provide communication to teams as appropriate. What You Bring Experience and Education: Bachelor's degree or diploma in Computer Science, Engineering, Information Systems, or related field Certificate in Data Engineering is an asset 4+ years' 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 Excellent communication and teamwork skills Can lead teams, train others, and work independently Self-motivated, organized, and analytical Note: An Intermediate employee has intermediate experience, able to handle more complex tasks independently, and often provides guidance to junior team members. Licenses and Certifications: A certificate in Data Engineering is a plus. Other Role Requirements: Strong project, organizational, and time management skills Excellent written, verbal, and presentation communication Skilled in documentation, facilitation, and negotiation Effective at collaborating and influencing stakeholders at all levels Experience leading teams and training others Self-motivated, organized, and analytical Capable of solving complex problems and meeting deadlines under pressure Eager to learn about the business Work arrangement: Remote first Occasional travel to Edmonton, Calgary, or Red Deer may be necessary as part of this position. Why Servus? Working for Servus has outstanding benefits. In addition to standard benefits like health and wellness, vacation and retirement savings programs, we also provide other important benefits such as: Competitive compensation including performance-based incentive pay and profit share Training & Development Opportunities Career Advancement Potential Flexible work options Meaningful work towards individual and corporate goals  Opportunities to get involved and give back through an employee volunteer program At Servus, our employees are also members. This means you'll have all the benefits of being a member of the credit union including profit sharing, voting for the board of directors, and all of the financial services we provide…with a few additional perks! What happens next? We thank all applicants for their interest. Please note applications will only be accepted online and only those applicants under consideration will be contacted. At Servus Credit Union, we believe in being purposefully cooperative and working together to create a culture of Belonging for everyone. We are committed to an inclusive, equitable, and accessible workplace where everyone is valued, respected, and supported. We encourage applications from individuals of all backgrounds, and accommodations are available during every stage of the hiring process upon request. Your skills, passion and curiosity may find they belong at Servus, so even if you don't check every box, we encourage you to apply! Employment Eligibility: The selected candidate(s) must successfully pass a criminal background check, reference check and credit check to qualify for hire by Servus Credit Union. Qualified applicants are invited to apply online. We thank all applicants for their interest. Please note applications will only be accepted online and only those applicants under consideration will be contacted

Qualifications

• Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
• Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Contributes to engineering and architectural documentation.
• Tests the reliability and performance of each part of a data ecosystem.
• Design and build data integrations and data quality framework.
• Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.