Data Engineer

Velosio•UNAVAILABLE, UNAVAILABLE

About The Position

Velosio is seeking a Microsoft Fabric Data Engineer to support the design, development, and delivery of modern data solutions across the Microsoft ecosystem. The role works alongside senior engineers, architects, analysts, and client stakeholders to build reliable data pipelines, organize and transform data, support Microsoft Fabric environments, and deliver business-ready data products. It is suited to an early- to mid-career engineer with a strong technical foundation who wants to develop consulting, architecture, and Microsoft Fabric expertise. The position is client-facing and includes participating in discovery sessions, assessments, technical workshops, demonstrations, reviews, and project meetings. The engineer builds and supports Microsoft Fabric and related Azure data solutions, integrations, and AI-ready data, while following established standards for architecture, security, governance, testing, monitoring, and deployment. Success is measured by the reliability and timely delivery of documented data solutions, clear communication of risks and progress, effective collaboration, ownership of assigned work, and continued growth in Microsoft Fabric and Azure capabilities.

Requirements

2 to 5 years of experience in data engineering, data integration, analytics engineering, business intelligence, or data platform delivery.
Hands-on experience building data pipelines, integrations, transformations, or data models in a professional, internship, consulting, or project environment.
Working knowledge of Microsoft Fabric or comparable Azure data technologies, and interest in developing deeper Fabric expertise.
Solid SQL skills and practical experience with at least one programming language, preferably Python.
Understanding of ETL and ELT concepts, data warehousing, dimensional modeling, APIs, file-based integrations, and common data-loading patterns.
Ability to test and troubleshoot pipelines, transformations, data-quality issues, and integration failures using logs and established support processes.
Basic familiarity with Git, source control, deployment processes, or DevOps practices for data solutions.
Basic understanding of cloud security concepts, including identities, permissions, role-based access, secrets, and data protection.
Clear written and verbal communication skills, including documenting technical work and explaining issues to technical and nontechnical audiences.
Strong problem-solving skills, attention to detail, curiosity, accountability, and willingness to ask questions and learn from senior team members.
Ability to manage assigned tasks across multiple priorities and communicate progress, blockers, and risks in a timely manner.

Nice To Haves

Exposure to PySpark.
Experience with Microsoft Fabric capabilities such as OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, notebooks, or Power BI.
Exposure to data governance, lineage, cataloging, quality, or Microsoft Purview.
Consulting, professional services, or client-facing project experience.
Exposure to Power BI semantic models, DAX, Direct Lake, Azure AI Search, Microsoft Foundry, Azure OpenAI, or AI-ready data patterns.
Microsoft certifications such as DP-700, DP-600, or relevant Azure fundamentals credentials; these may also be pursued after hire.

Responsibilities

Participate in client discovery sessions and technical workshops to understand business needs, data sources, reporting requirements, and challenges.
Document current-state environments, data flows, integration points, technical issues, and improvement opportunities as part of data and analytics assessments.
Work with senior engineers and architects to translate requirements into Microsoft Fabric designs and delivery tasks.
Build and maintain Microsoft Fabric solutions using OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, notebooks, and related Azure data services.
Develop, test, deploy, monitor, and troubleshoot data pipelines using SQL, Python, PySpark, APIs, and orchestration tools.
Help implement medallion architectures and dimensional models across bronze, silver, and gold layers.
Create and maintain technical documentation, data mappings, pipeline specifications, runbooks, testing records, and knowledge-transfer materials.
Apply established practices for data quality, security, access, monitoring, error handling, logging, and deployment.
Support data governance, lineage, cataloging, metadata, and access-control activities using Microsoft Purview and related capabilities.
Collaborate with Power BI developers, analytics engineers, architects, analysts, administrators, and client teams to deliver trusted data products.
Build and support integrations involving Microsoft Dynamics 365, Dataverse, ERP, CRM, databases, files, APIs, and other business platforms.
Assist with AI-ready data solutions by preparing governed, reliable data for Microsoft Foundry, Azure AI Search, data agents, and other AI scenarios.
Participate in client demonstrations, technical reviews, and project meetings; communicate progress, questions, risks, and recommended next steps.
Troubleshoot pipeline, performance, data-quality, and reliability issues, escalating complex concerns when needed.
Continue developing Microsoft Fabric, Azure, Power BI, and AI expertise through delivery, training, and certification.
Deliver accurate, reliable, tested, documented data pipelines, transformations, and integrations on schedule, following architecture, security, governance, and development standards.
Raise issues, dependencies, risks, and questions early; complete practical documentation and knowledge-transfer materials; take ownership of assigned deliverables and build independence over time.