As a Senior Data Engineer you will be the subject matter expert in Microsoft Fabric to support the evolving data needs of Central 1. The Senior Data Engineer is responsible for designing, implementing, and optimizing cloud-based data pipelines and data solutions that enable secure, compliant, and actionable insights, supporting our mission of delivering exceptional financial services to our members.
This role collaborates with product owners, data teams, financial analysts, and IT stakeholders to build scalable data platforms that empower data-driven decisions, enhance member experiences, and ensure regulatory compliance.
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 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 DevOps 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 ServiceNow 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.
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.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
6+ years of experience in data engineering roles, with hands-on experience in Microsoft Fabric and Azure data technologies.
Strong proficiency in Azure Data Factory (ADF), Microsoft Fabric, SQL, and Azure Storage services.
Proficiency in SQL and Python\PySpark for developing data transformation and processing workflows.
Strong understanding of ETL/ELT concepts, data pipeline design, and orchestration patterns.
Experience integrating financial systems and handling sensitive data (e.g., PII) in compliance with regulatory and security standards.
Experience with collaboration and delivery tools such as Jira, Confluence, and Azure DevOps.
Strong proficiency with Git and Azure DevOps, including repository management, branching strategies, pull requests, peer reviews, merge conflict resolution, release management, and CI/CD deployment practices supporting enterprise data engineering solutions.
