Senior Data Engineer

Senior Data Engineer, 6 month contract-(Hybrid)

Job Summary:

Central 1 is looking for a Data Engineer to join our team on a 6-month term basis. In this role, you'll play an important part in supporting our evolving data needs and helping shape how we use Microsoft Fabric and modern cloud-based data solutions across the organization. As a Data Engineer, you'll be a key Microsoft Fabric subject matter expert, designing, building, and optimizing secure, reliable, and compliant data pipelines and solutions that turn data into actionable insights.

You'll work closely with product owners, data teams, financial analysts, and IT partners to create scalable data platforms that support smarter decision-making, enhance member experiences, and help Central 1 continue delivering exceptional financial services.

This opportunity may have the opportunity to extend beyond 6 months

• Design, develop, and maintain data pipelines using Microsoft Fabric and Azure Data Factory (ADF), enabling scalable, efficient, and reliable data ingestion, transformation, and orchestration across the data platform
• Ensure data security and compliance by implementing best practices such as role-based access control (RBAC), encryption (at rest and in transit), and secure credential management (e.g., Azure Key Vault), while adhering to organizational policies and regulatory requirements
• Collaborate with data governance stakeholders to enforce data quality standards, lineage tracking, and metadata management within the Azure ecosystem.
• Design and implement monitoring solutions using Azure-native services (e.g., Azure Monitor, Log Analytics, etc.) to ensure platform reliability, performance visibility, and proactive issue detection
• Deliver data solutions in alignment with approved architecture, adhering to established design standards, governance frameworks, and the prescribed Azure technology stack to ensure consistency, scalability, and maintainability
• Collaborate cross-functionally with Data Architects, Business Stakeholders, and data teams to translate business requirements into robust technical solutions, providing informed input into design decisions and best practices
• Develop, configure, and maintain CI/CD pipelines using Azure Dev Ops to enable efficient, repeatable, and automated deployment of data solutions across all environments
• Produce and maintain comprehensive documentation in Confluence, ensuring solutions, processes, and configurations are clearly documented to support ongoing operations and knowledge sharing
• Ensure adherence to ITIL-based processes for incident and change management, using tools such as Service Now to triage, track, and resolve incidents in a timely and structured manner
• Proactively drive operational excellence by identifying recurring issues, implementing preventative measures, and optimizing workflows to reduce system failures and improve platform stability
• Conduct peer code reviews through pull requests to ensure code quality, consistency, adherence to standards, and knowledge sharing across the team
• Develop, maintain, and optimize Power BI solutions, including dashboards and reports, efficient data models, and DAX measures to deliver actionable business insights
• Deliver against project commitments by contributing to the design, development, and implementation of data engineering solutions, ensuring alignment with timelines, quality standards, and business objectives
• Perform additional duties as required to deliver exceptional service and support the achievement of Central's business objectives
• Will be required to participate in 24x7 on call responsibilities

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 4+ years of experience in data engineering roles, with hands‑on experience in Azure cloud platforms.
• Strong proficiency in Azure Data Factory (ADF), Microsoft Fabric, T‑SQL, and Azure Storage services.
• Proficiency in SQL and Python for developing data transformation and processing workflows.
• Experience designing and building data lakes and data warehouses, ideally within payments or financial services environments.
• Strong understanding of…