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Trility Consulting
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Senior Data Consultant - Azure Synapse to Microsoft Fabric Migration

Trility Consulting
United StatesUnited States
Full-time
Not Disclosed
Senior-Level
VT

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Job Description

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Key Skills Required

Master these to land this role

Spark SQLCI/CDPySparkAzure SynapseMicrosoft Fabric

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Trility Consulting is seeking an experienced Senior Data Consultant to support a client engagement focused on modernizing an existing Azure Synapse data platform and migrating prioritized workloads to Microsoft Fabric.

In this role, you'll partner with Trility consultants and client engineers to pressure-test and refine the Fabric architecture, build reusable, metadata-driven ingestion frameworks, and migrate data workloads into a modern lakehouse environment. You'll develop scalable data pipelines, implement validation processes to ensure migration accuracy, and establish automated CI/CD workflows that support reliable deployment from development through production.

This engagement follows Trility's collaborative Coach-and-Contribute delivery model. You'll work hands-on alongside client engineers, contribute to architectural decisions, and help establish repeatable patterns that enable the team to maintain and extend the platform independently. Experience using Claude Code as part of an AI-assisted development workflow is essential to this engagement.

Your Responsibilities

  • Evaluate and refine the existing Microsoft Fabric architecture, including metadata structures, table-level event triggering, and reusable ingestion patterns
  • Design and implement a metadata-driven ingestion framework that allows new tables and sources to be onboarded through configuration rather than custom development
  • Migrate prioritized data sources and workloads from Azure Synapse into Microsoft Fabric
  • Develop and orchestrate Fabric data pipelines and Spark notebooks using PySpark and Spark SQL
  • Analyze existing Azure Synapse pipelines, including complex and nested workflows, to understand dependencies and translate existing processing logic into Fabric solutions
  • Build data validation and reconciliation processes to verify migration accuracy, including duplicate detection, key alignment, and record-level comparisons between Synapse and Fabric
  • Analyze source-specific loading requirements and recommend appropriate full-load, incremental, or change data capture (CDC) patterns
  • Implement Git-based CI/CD and automated environment promotion for Fabric artifacts, including pipelines and notebooks, using GitHub Actions, Azure DevOps, or similar tooling
  • Leverage Claude Code to define implementation specifications, accelerate development, and review AI-generated code for quality, correctness, and maintainability
  • Evaluate data dictionary, metadata, and lineage requirements, including potential catalog solutions such as Microsoft Purview
  • Collaborate with client engineers through paired development, code reviews, and knowledge-sharing sessions to establish sustainable engineering standards
  • Apply data engineering best practices related to performance, testing, monitoring, documentation, security, and operational support

What You Bring

  • 5+ years of experience working with Azure Data Services, including Microsoft Fabric, Azure Data Factory, Databricks, or Synapse
  • Hands-on Microsoft Fabric experience in production environments, including lakehouses, pipelines, notebooks, medallion architecture, workspaces, and capacity management
  • Strong experience building and maintaining production ETL/ELT pipelines and reusable data ingestion frameworks
  • Demonstrated experience designing and implementing a metadata-driven ingestion framework, including configuration-based onboarding and extensible processing patterns
  • Experience developing Spark notebooks and data transformation workflows using PySpark and Spark SQL
  • Strong SQL skills for data transformation, validation, and performance tuning, including the ability to read and understand existing T-SQL logic
  • Experience working with Azure Synapse, including analyzing existing pipelines and understanding complex data processing dependencies
  • Experience implementing medallion architecture patterns (Bronze, Silver, Gold)
  • Experience designing and implementing Git-based CI/CD workflows for data platform artifacts using GitHub Actions, Azure DevOps, or similar tooling
  • Hands-on experience using Claude Code for AI-assisted software development, including directing code generation, working across multiple files, and critically reviewing generated code
  • Experience validating data migrations and ensuring data quality, accuracy, and consistency across source and target systems
  • Experience integrating data from REST APIs, relational databases, and structured or semi-structured data sources
  • Familiarity with data governance, lineage, metadata management, and data catalog concepts
  • Ability to collaborate effectively with technical teams, challenge existing approaches constructively, and participate in client-facing technical discussions
  • Strong written and verbal communication skills

Preferred Experience

  • Experience migrating data platforms or workloads from Azure Synapse to Microsoft Fabric
  • Experience working with Oracle and DB2 data sources
  • Experience implementing incremental ingestion, change data capture (CDC), and source-specific loading strategies
  • Experience developing data reconciliation and validation frameworks for large-scale migrations
  • Experience evaluating Microsoft Purview or other data catalog and lineage solutions
  • Experience working within consulting or professional services environments

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Trility Consulting

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Trility Consulting (operating at trility.io) is a business and AI-driven consulting firm platform engineered for integrated, end-to-end technology solutions. Founded in Not specified by Not specified and headquartered in Clive, Iowa, Trility Consulting helps mid-market to enterprise-sized companies define, design, and deliver custom solutions. Under the hood, the firm leverages AI-driven consulting to simplify, automate, and secure each iteration. This allows mid-market to enterprise-sized companies to accelerate innovation and modernization through data audits, stakeholder interviews, and business application demos.

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