Principal Programmer / Analyst 2

Description

As a Fabric Data Analytics Engineer, you will join our Data Analytics team as a Subject Matter Expert (SME) to design, develop, and manage enterprise-scale data solutions on Microsoft Fabric. You will be responsible for building modern data platforms leveraging Lakehouse, Data Warehouse, Data Pipelines, and Real-Time Analytics, enabling scalable, governed, and high-performing data ecosystems

Responsibilities

Key Duties include, but not limited to:

  • Design, develop, and implement end-to-end data solutions using Microsoft Fabric components such as Lakehouse, Data Factory (Pipelines), Dataflows Gen2, Warehouse, and Notebooks.
  • Build and maintain scalable data ingestion, transformation, and orchestration pipelines for structured and unstructured data.
  • Develop and implement robust data models and semantic layers to support downstream analytics, including Power BI.
  • Ensure data quality, reliability, and performance optimization across all Fabric workloads.
  • Manage and optimize Delta Lake tables and Lakehouse architectures, including partitioning, indexing, and storage optimization.
  • Collaborate with IT, analytics, and business teams to gather requirements, define architecture, and deliver enterprise data solutions.
  • Implement and maintain data governance, lineage, security, and compliance frameworks using Fabric and Purview integration.
  • Build and maintain real-time and near-real-time data processing solutions using Fabric Event Streams and streaming datasets.
  • Design and manage data warehousing solutions within Fabric Warehouse for high-performance analytics.
  • Develop and maintain documentation, including data architecture diagrams, data dictionaries, pipeline flows, and operational runbooks.
  • Integrate data from various sources, including ERP systems, APIs, databases, files, and external platforms, into Fabric.
  • Monitor and troubleshoot data pipelines, workloads, and capacity performance to ensure SLAs are met.
  • Enable and support self-service analytics by preparing curated datasets and collaborating with Power BI developers.
  • Implement CI/CD and DevOps practices for data pipelines and Fabric artifacts.
  • Optimize storage and compute utilization to manage cost and capacity planning within Fabric environments.
  • Work in Agile methodology to design, develop, test, and deploy data engineering solutions and enhancements.
  • Continuously stay updated with Microsoft Fabric advancements, new features, and best practices.

Required Experience and Skills

  • SKILLS AND EDUCATION REQUIREMENTS
  • Bachelor’s degree in Computer Science, Information Technology, or a related field.
  • 5+ years of experience in data engineering, data platforms, or enterprise analytics systems.
  • 5+ years of experience in modern data platforms such as Azure Data Services, Microsoft Fabric, or equivalent.
  • Strong experience with:
  • Microsoft Fabric (Lakehouse, Pipelines, Warehouse, Notebooks)
  • SQL and data modeling (dimensional and normalized models)
  • PySpark / Spark (preferred within Fabric notebooks)
  • Solid understanding of:
  • Data warehousing concepts and architectures
  • ETL/ELT frameworks and pipeline orchestration
  • Distributed data processing systems
  • Experience integrating and supporting Power BI semantic models and datasets.
  • Strong knowledge of data governance, security, and access control models.
  • Excellent problem-solving, analytical, and performance optimization skills.
  • Strong communication and stakeholder management skills.
  • Ability to work in fast-paced, cross-functional, and agile environments.

#PR1

Desired Experience and Skills

  • Knowledge of cloud platforms (Azure, AWS) and containerization (Docker, Kubernetes).
  • Experience with data analytics and reporting tools (Power BI, Tableau).
  • Familiarity with security best practices and compliance standards (SOX, GDPR).
  • Excellent problem-solving, communication, and leadership skills.

See also

Data Analytics jobs by country — openings, pay and top skills →

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