Data Engineer - Microsoft Fabric

Integra • Dallas, TX

2d • Onsite

About The Position

The Data Engineer builds data pipelines that connect Integra’s core business systems to its enterprise data platform, making trusted data available across the organization. Working hands-on in Microsoft Fabric, the engineer ingests, transforms, organizes, and integrates data from ERP, CRM, HR, manufacturing, construction, and other operational systems. The role builds and maintains Bronze and Silver data layers and prepares data for downstream analytics and business solutions across Finance, HR, Marketing, Engineering, Technology, and Operations.

The engineer partners with Data Architecture, Analytics, Power BI, and business teams to understand how data is created and used, identify gaps between systems, and turn complex source data into consistent, scalable, trusted data products. This position is 100% onsite in the far North Dallas/Plano area.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related discipline, or equivalent professional experience.
• At least 4 years of professional experience in data engineering, data integration, business intelligence engineering, or a related discipline.
• Hands-on experience building production data pipelines and cloud-based analytics solutions.
• Experience working with relational databases, APIs, files, and enterprise application data.
• Strong analytical, troubleshooting, documentation, and communication skills.
• Ability to work independently and collaborate effectively with architects, engineers, analysts, and business stakeholders.
• Technical experience with Microsoft Fabric Data Factory, Pipelines, Lakehouse, Warehouse, OneLake, notebooks, Spark runtime, Dataflows Gen2, Delta tables, Direct Lake, workspace security, deployment pipelines, monitoring, and capacity awareness.
• Advanced SQL, relational data modeling, Python, PySpark, Apache Spark, Delta Lake, Parquet, ETL and ELT patterns, metadata-driven frameworks, CDC, watermarking, incremental loading, reconciliation, observability, and performance tuning.
• Experience with Azure Data Lake Storage Gen2, Azure Data Factory, Azure SQL Database or comparable platforms, Microsoft Entra ID, service principals, managed identities, Azure Key Vault, Azure DevOps, Git, CI/CD, Azure Monitor, and Log Analytics.
• Knowledge of Bronze, Silver, and Gold layers; dimensional modeling; canonical data models; source-to-target mapping; lineage; metadata; business glossaries; data dictionaries; and Microsoft Purview or comparable governance tooling.

Nice To Haves

• Experience with Oracle Fusion ERP, Deltek Costpoint, SAP S/4HANA, Primavera P6, Procore, Autodesk Construction Cloud, Salesforce, or manufacturing and product lifecycle systems.
• Knowledge of financial and ERP domains including general ledger, AP, AR, procure-to-pay, order-to-cash, project accounting, project costing, revenue recognition, budgeting, forecasting, and financial reporting.
• Knowledge of project controls, construction, manufacturing, and supply-chain data domains.

Responsibilities

• Build and maintain data pipelines using Fabric Data Factory, Fabric Pipelines, Dataflows Gen2, and notebooks.
• Develop and support Fabric Lakehouse and Warehouse solutions using OneLake and Delta tables.
• Implement scalable Bronze, Silver, and Gold processing patterns aligned with Medallion Architecture.
• Develop Spark, PySpark, SQL, and notebook-based transformations for structured and semi-structured data.
• Use Fabric shortcuts, mirroring, and ingestion patterns suited to source systems and workloads.
• Optimize Fabric workloads for performance, reliability, concurrency, and capacity consumption, and support Direct Lake semantic models and downstream Power BI requirements.
• Develop metadata-driven ingestion frameworks for databases, files, APIs, SaaS applications, and enterprise systems.
• Implement full-load, incremental-load, watermark, and Change Data Capture patterns.
• Build resilient pipelines with parameterization, dependency management, retry logic, logging, and alerting.
• Integrate data from Oracle Fusion ERP, Deltek Costpoint ERP, Primavera P6, Procore, Salesforce, manufacturing systems, and other operational platforms.
• Implement reconciliation, source-to-target validation, audit controls, restartable processing, and technical metadata management.
• Transform raw source-aligned Bronze data into standardized and validated Silver data structures.
• Implement source-to-canonical mappings for finance, projects, procurement, suppliers, customers, employees, organizations, scheduling, and manufacturing domains.
• Build Gold data products and dimensional models for enterprise reporting and analytics.
• Implement schema enforcement and evolution, deduplication, data-quality rules, quarantine processes, and exception reporting.
• Use Delta Lake capabilities including MERGE, ACID transactions, time travel, optimization, and controlled retention.
• Create reusable engineering components, frameworks, templates, and coding standards.
• Implement workspace, item, OneLake, SQL endpoint, and data access controls with platform and security teams.
• Use Microsoft Entra ID, managed identities, service principals, Azure Key Vault, and least-privilege access patterns.
• Support Microsoft Purview cataloging, classification, lineage, business glossary, and data-discovery processes.
• Manage source code through Git and Azure DevOps, including branching, pull requests, code reviews, release pipelines, and deployment practices.
• Support separate development, test, and production environments using deployment pipelines and controlled configuration.
• Develop monitoring and operational dashboards for pipeline health, failures, runtimes, data freshness, quality, and capacity consumption.
• Partner with the Data Architect to implement enterprise architecture, canonical modeling, governance, and integration standards.
• Work with functional subject-matter experts and data stewards to understand source data, business rules, and validation requirements.
• Collaborate with Power BI developers and Analytics Engineers to deliver trusted semantic models and data products.
• Create technical documentation, runbooks, data dictionaries, source-to-target mappings, and operational support procedures.
• Troubleshoot production issues, perform root-cause analysis, and implement permanent corrective actions.
• Participate in peer reviews, sprint planning, estimation, testing, release management, and continuous improvement.

Benefits

• Competitive pay with incentive opportunities that recognize results and contributions.
• Medical, dental, and vision coverage.
• Life and disability insurance programs.
• Voluntary benefits options.
• Generous paid time off.
• Education assistance and tuition support.
• Retirement and savings programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level