Senior Data Engineer(Microsoft Fabric)

Position Summary

USEReady is seeking a hands-on, technical Lead / Senior Data Engineer (510 years experience) to design, build, and optimize scalable data pipelines and modern cloud data platforms. The ideal candidates are seasoned professionals with deep experience working across Operations, Engineering, and Finance data, bringing specialized knowledge of SCADA, PI systems, historians, telemetry, IoT, and OT/IT source system integration. This role will focus heavily on execution across Microsoft Fabric, Azure data services, Databricks, and Snowflake.

Key Responsibilities

• 5+ years of progressive technology experience, including 8+ years leading enterprise data-platform, data-engineering, cloud, or related technical capabilities.
• Demonstrated experience leading teams that support modern cloud data architectures such as Microsoft Fabric, Azure lakehouse/warehouse platforms, Databricks, Snowflake, or comparable technologies.
• Own data acquisition capabilities and reference patterns for batch ETL/ELT, change data capture, APIs, file transfer, event streaming, near-real-time ingestion, and operational/industrial data.
• Define enterprise patterns for operational and industrial data acquisition, contextualization, integration, and scalability across historian, telemetry, SCADA, IoT, and future operational data platforms.
• Lead the design and delivery of scalable Bronze, Silver, Gold, and product-serving data layers with clear transformation boundaries, access patterns, quality controls, lifecycle management, and alignment to governed consumption patterns.
• Define and operate enterprise data access services, including APIs, event-driven interfaces, governed data sharing, curated consumption endpoints, and reusable access patterns that enable analytics, applications, AI, and external partner integration.
• Enable self-service data platform capabilities through standardized onboarding, reusable engineering patterns, templates, documentation, developer portals, and governed access mechanisms.
• Establish enterprise data-management capabilities covering metadata, catalog, lineage, data quality, master and reference data, retention, archival, certification, and governed reuse.
• Define enterprise data-lifecycle standards covering acquisition, retention, archival, discovery, disposition, and compliance requirements across structured and unstructured data assets.
• Embed data security into the platform through identity and access management, role-based and attribute-based controls, private connectivity, encryption, secrets management, audit logging, data classification, and policy enforcement.
• Ensure data ingestion and analytical workloads are engineered to protect the performance, availability, and recoverability of operational source systems

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Management Information Systems, Data Engineering, or a related technical field; equivalent relevant experience will be considered.
• Demonstrated experience leading teams that support modern cloud data architectures such as Microsoft Fabric, Azure lakehouse/warehouse platforms, Databricks, Snowflake, or comparable technologies.
• Deep experience with the Microsoft Azure data ecosystem, including data storage, ingestion, integration, analytics, identity, networking, security, monitoring, DevOps, and platform operations capabilities.
• Strong experience designing and operating data acquisition capabilities across ETL/ELT, change data capture, APIs, event streaming, batch, and near-real-time processing.
• Experience defining enterprise data access patterns, including APIs, governed data sharing, reusable consumption services, and product-serving data layers.
• Experience establishing enterprise data-management practices for metadata, lineage, quality, master/reference data, lifecycle, and governed consumption.
• Experience implementing data-security architectures, including identity, access controls, network isolation, encryption, secrets, auditing, classification, and compliance controls.
• Experience operating production data platforms with defined service levels, monitoring, incident management, support models, backup and recovery, performance management, and cost accountability.
• Experience implementing engineering discipline through CI/CD, source control, automated testing, deployment automation, environment management, and infrastructure as code.
• Experience managing cloud platform economics, consumption optimization, capacity forecasting, cost governance, or FinOps practices.