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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Data Engineer / Data Architect - **Company:** Integra - **Location:** Dallas, TX, United States - **Experience:** Expert - **Salary:** $212,700.0 - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Software Code Optimization, Information Systems, Costpoint, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Python (Programming Language), Project Management Software, Metadata, Meta-Data Management, Performance Tuning, Primavera, Cloud Services, Salesforce.Com, Oracle Fusion Middleware, Enterprise Data Management, Parquet, Data Logging, Enterprise Software Applications, Azure Data Factory, Sql Optimization, Apache Spark, Technical Debt, Change Data Capture, Data Layers, Microsoft Fabric, Data Lakes, Pyspark, Storage Technologies, Information Technology, Data Lineage, Star Schema, SAP S/4HANA, Operational Systems, Data Management, Api Design, Cloud Optimization, Autodesk Autocad, Data Pipelines, Databricks - **Published:** November 6, 2026 - **Apply:** https://www.adzuna.com/details/5940192846 ## About the Role * Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline, or equivalent professional experience. * 8+ years of experience in Data Engineering, Data Architecture, or a related discipline. * Proven experience designing and implementing enterprise-scale cloud data platforms and modern Lakehouse architectures. * Strong hands-on experience with Azure data services, advanced SQL, Python, PySpark, Spark, Delta Lake, Parquet, ETL/ELT design, metadata-driven frameworks, and performance optimization. * Practical experience with Microsoft Fabric and/or Azure Databricks, including platform-specific Lakehouse, pipeline, orchestration, governance, and semantic modeling capabilities. * Experience integrating data from multiple enterprise applications and business domains. * Strong knowledge of canonical, dimensional, and star schema modeling; conformed dimensions; master data management; governance; lineage; and metadata management. * Strong communication and stakeholder management skills, with the ability to translate business requirements into scalable technical solutions. Preferred Qualifications * Experience with Oracle Fusion ERP, Deltek Costpoint, Primavera P6, Procore, Salesforce, SAP S/4HANA, Autodesk Construction Cloud, or comparable enterprise platforms is preferred. * Knowledge of financial and ERP, project controls, construction and engineering, or manufacturing data domains is preferred. ## Description The Senior Data Engineer / Data Architect designs, implements, and evolves the enterprise data platform, with a focus on a modern Azure-based Lakehouse environment that integrates data across ERP, scheduling, construction management, manufacturing, HR, CRM, and operational systems. This hands-on role establishes scalable data architecture and engineering standards, develops canonical and semantic data models, and delivers trusted data products that support ERP modernization, enterprise reporting, advanced analytics, and self-service business intelligence. The position combines strategic architecture responsibilities with direct technical contribution across Microsoft Fabric, Azure Databricks, data integration, governance, quality, lineage, observability, and platform optimization. What you will do? Enterprise Data Architecture * Define and maintain enterprise data architecture standards, best practices, and reusable patterns that support application modernization and future system migrations. * Design scalable Bronze, Silver, and Gold Lakehouse architectures and enterprise semantic models for reporting, analytics, and governed self-service BI. * Develop and govern canonical data models spanning ERP, CRM, scheduling, construction management, manufacturing, HR, and other operational domains. * Establish standards for data integration, metadata, lineage, data quality, governance, security, and trusted business definitions. Data Engineering & Platform Delivery * Design and implement metadata-driven ingestion and processing frameworks for structured, semi-structured, and API-based data sources. * Build scalable ELT pipelines, Change Data Capture processes, incremental loading strategies, reconciliation controls, and audit capabilities. * Implement monitoring, alerting, logging, observability, and operational support frameworks across the data platform. * Optimize platform performance, scalability, reliability, storage architecture, and cloud cost management. Lakehouse Engineering * Design and implement enterprise Lakehouse solutions using Microsoft Fabric and/or Azure Databricks. * Build and maintain Delta Lake-based Bronze, Silver, and Gold data layers and develop Spark and PySpark transformation pipelines. * Implement data quality controls, lineage tracking, governance processes, job orchestration, and reusable engineering standards. * Evaluate platform options based on business requirements, scalability, operational considerations, and cost optimization. Enterprise Systems Integration * Integrate data from ERP, scheduling, project controls, construction management, manufacturing, HR, CRM, and other operational platforms. * Define and maintain source-to-canonical mappings across enterprise applications, including Oracle Fusion ERP, Deltek Costpoint, Primavera P6, Procore, Salesforce, and comparable systems. * Partner with business and technology stakeholders to translate requirements into scalable, supportable data solutions. * Support ERP modernization and broader enterprise transformation initiatives through reliable data integration and architecture. Analytics Enablement & Data Governance * Partner with Finance, Operations, Project Controls, and Business Intelligence teams to support enterprise reporting and analytics platforms. * Define business metrics, KPIs, semantic models, conformed dimensions, and data standards in alignment with stakeholder requirements. * Enable reusable, governed, and trusted data products that support self-service analytics and executive reporting. * Improve enterprise data quality, governance, lineage, metadata management, and observability across the platform. Technical Leadership & Delivery Standards * Operate effectively as both an enterprise data architect and a hands-on senior engineering contributor. * Provide technical guidance on architecture decisions, engineering practices, performance tuning, and platform reliability. * Promote scalable patterns that reduce technical debt and support future business growth. * Communicate technical concepts, risks, dependencies, and recommendations clearly to business and technology stakeholders.