Senior Data Engineer

Senior Data EngineerLocation: Remote Clearance Level: Active SecretOverviewRackner is seeking a Senior Data Engineer to lead the design, development, optimization, and operation of enterprise data pipelines and data platform components within the Microsoft Fabric environment.The Senior Data Engineer will provide hands-on technical leadership across data ingestion, transformation, platform administration, security, automation, and deployment activities. This role will be responsible for implementing scalable medallion architectures, establishing reliable development and deployment practices, and ensuring data platforms meet security, availability, performance, and data quality requirements.The Senior Data Engineer will also mentor Data Engineers and Associate Data Engineers, provide technical problem-solving support, and help establish engineering standards and best practices across data workstreams.Responsibilities Lead the design, development, and optimization of enterprise data ingestion pipelines, transformation logic, and data platform components within Microsoft Fabric Design and implement scalable ETL and ELT architectures supporting structured and semi-structured enterprise data Configure, administer, and maintain Microsoft Fabric environments, including: Tenant administration Workspace architecture Capacity management Security configuration Environment governance Implement and maintain Bronze, Silver, and Gold medallion architecture layers Develop data transformation processes incorporating schema validation, cleansing, normalization, enrichment, and reconciliation Establish data quality monitoring, validation controls, automated testing, and alerting for pipeline and data-quality failures Design and implement development, test, staging, and production environment separation Build and maintain CI/CD deployment pipelines for data platform components, pipelines, notebooks, configurations, and related artifacts Implement infrastructure-as-code approaches for repeatable, version-controlled data platform deployments Develop and optimize Spark, PySpark, SQL, and related data-processing workloads Configure and maintain data security controls, including: Encryption Role-Based Access Control (RBAC) Microsoft Entra ID integration Privileged Identity Management Least-privilege access controls Support secure integration between Microsoft Fabric and enterprise source systems Design and support hybrid connectivity between on-premises and cloud environments Troubleshoot complex pipeline, platform, performance, connectivity, and data-quality issues Optimize pipelines and data workloads for performance, scalability, reliability, and cost Support disaster recovery and business continuity planning for data platforms and pipelines Develop, document, and execute rollback, recovery, and restoration procedures Conduct recovery and rollback testing to validate continuity procedures Establish reusable engineering patterns, standards, and technical documentation for data platform implementation Collaborate with Data Architects, Data Governance Specialists, cybersecurity teams, application teams, and source-system owners to define technical solutions Participate in architecture reviews and provide technical recommendations for data platform modernization and integration efforts Mentor mid-level and Associate Data Engineers Review technical implementations and provide guidance on pipeline design, code quality, performance, security, and maintainability Provide senior-level technical problem-solving support for complex data engineering challenges Support knowledge transfer and operational transition of implemented data platform capabilities Qualifications Significant experience designing and implementing enterprise data pipelines, ETL/ELT processes, and cloud-based data platforms Hands-on experience with Microsoft Fabric Experience administering or configuring enterprise cloud data environments Strong experience with Azure Data Factory or comparable data integration technologies Strong SQL proficiency Experience with Spark and PySpark for large-scale data processing and transformation Experience implementing enterprise ETL/ELT frameworks Experience designing and implementing medallion architectures using Bronze, Silver, and Gold data layers Experience with schema validation, data cleansing, normalization, reconciliation, and data quality controls Experience developing CI/CD pipelines for data platform deployments Experience implementing infrastructure-as-code Experience with source control, automated deployment, and environment promotion processes Understanding of cloud security principles, including RBAC, identity integration, encryption, and least-privilege access Experience troubleshooting complex data pipeline, platform, and integration issues Experience supporting production data environments with availability, reliability, and performance requirements Strong technical documentation and communication skills Experience me