[Hiring] Senior Data Engineer @Architecture in Motion Inc.

Role Description

AIM is seeking a Senior Data Engineer (AI & LLM Solutions) to design, develop, and optimize modern data platforms that support analytics, artificial intelligence, machine learning, and Generative AI solutions. This is a hands-on senior role requiring strong expertise in Microsoft Fabric, Azure Data Services, Azure Databricks, Python, PySpark, and enterprise data architecture, along with practical experience supporting AI and LLM initiatives.

The ideal candidate will build scalable and secure data solutions while enabling advanced AI capabilities, including:

• Retrieval-Augmented Generation (RAG)
• Vector search
• Azure OpenAI
• Copilot
• Enterprise LLM solutions

The successful candidate will work closely with Solution Architects, AI Engineers, Cloud Engineers, Data Scientists, and client stakeholders to deliver secure, scalable, and business-driven data platforms.

Key Responsibilities

• Modern Data Platform Development
  • Design and develop enterprise-scale data solutions using Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks.
  • Build and optimize scalable ETL/ELT pipelines for structured, semi-structured, and unstructured data.
  • Develop modern Lakehouse, Data Warehouse, and Medallion Architecture solutions.
  • Design and implement batch and real-time data processing frameworks.
  • Lead data modernization, migration, and integration initiatives from legacy platforms.
• AI, LLM & Data Enablement
  • Develop data foundations that support AI, Machine Learning, and Generative AI solutions.
  • Prepare, transform, and optimize datasets for AI applications, model training, and fine-tuning.
  • Design and implement Retrieval-Augmented Generation (RAG) architectures and vector search solutions.
  • Support Azure OpenAI, Microsoft Copilot, and enterprise LLM implementations.
  • Develop data pipelines and architectures that enable AI-driven applications.
  • Collaborate with Data Scientists and AI Engineers to operationalize AI and machine learning solutions.
• Advanced Data Engineering
  • Build distributed data processing solutions using PySpark and Spark SQL.
  • Develop automated data integration frameworks connecting APIs, SaaS applications, databases, and cloud services.
  • Design reusable data engineering frameworks, components, and standards.
  • Optimize large-scale workloads for performance, scalability, reliability, and cost efficiency.
  • Implement data quality, validation, monitoring, and error-handling processes.
• Data Governance & Security
  • Implement data governance and cataloging solutions using Microsoft Purview and related technologies.
  • Establish and maintain data lineage, classification, cataloging, and access controls.
  • Ensure data platforms align with enterprise security, privacy, and compliance requirements.
  • Support governance and security requirements across frameworks such as SOC 2, NIST, and CMMC.
  • Implement secure data access and protection practices across cloud data platforms.
• Reporting & Analytics Support
  • Design and support semantic data models for Power BI and enterprise analytics.
  • Enable self-service analytics while maintaining appropriate governance and data quality standards.
  • Support KPI frameworks, executive dashboards, reporting, and predictive analytics initiatives.
  • Collaborate with analytics teams to ensure reliable and high-quality data availability.
• Technical Leadership & Collaboration
  • Provide technical guidance and mentorship to junior and mid-level data engineers.
  • Participate in solution architecture, technical design reviews, and implementation planning.
  • Work directly with clients and stakeholders to understand requirements and translate business needs into scalable technical solutions.
  • Collaborate with cross-functional teams including AI Engineers, Cloud Engineers, Solution Architects, Data Scientists, and Business Analysts.
  • Participate in technical discussions and presales activities where required.
  • Develop technical documentation, engineering standards, and reusable implementation patterns.
• Support & Continuous Improvement
  • Troubleshoot and resolve data pipeline, platform, and integration issues.
  • Monitor and optimize data workloads and cloud resources.
  • Support enhancements, upgrades, and ongoing maintenance of data platforms.
  • Identify opportunities to improve data quality, automation, performance, and operational efficiency.
  • Stay current with emerging technologies in Microsoft Fabric, Azure, AI, Generative AI, and data engineering.

Qualifications

• Education: Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related discipline.
• Experience:
  • 8+ years of professional experience in Data Engineering, Data Platforms, or Cloud Data Solutions.
  • 5+ years of hands-on experience with Microsoft Azure Data Services.
  • Proven experience delivering enterprise-scale data, analytics, and AI solutions.
  • Strong experience working with modern cloud data platforms and data architectures.
  • Experience working within consulting, professional services, or enterprise environments.
  • Strong communication, stakeholder management, and problem-solving skills.
• Technical Skills:
  • Data Platform Technologies: Microsoft Fabric, Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage Gen2 (ADLS), Azure Databricks, Azure Event Hubs.
  • Data Warehouse & Lakehouse Architecture: Medallion Architecture.
  • Programming & Data Processing: Python, SQL, PySpark, Spark SQL, Kusto Query Language (KQL), REST API integrations, ETL/ELT development.
  • Databases: SQL Server, PostgreSQL, MySQL, NoSQL databases, Data modeling and optimization.
  • AI & Machine Learning: Azure OpenAI, Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases / Vector Search, Machine Learning Pipelines, NLP fundamentals, LLM integration patterns, AI-ready data architecture.
  • Analytics & Visualization: Power BI, Tableau, Semantic Models, Executive Reporting, KPI Frameworks.
  • Governance & Security: Microsoft Purview, Data Governance, Data Classification, Data Lineage, Data Cataloging, Access Control, Enterprise Security Standards, SOC 2, NIST, and CMMC awareness.
  • DevOps & Cloud Engineering: Azure DevOps, Git, CI/CD Pipelines, Infrastructure as Code concepts, Containerization concepts, Cloud resource optimization.

Preferred Certifications

• Microsoft Certified: Fabric Analytics Engineer Associate
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Certified: Azure Data Scientist Associate
• Microsoft Certified: Azure Solutions Architect Expert
• Databricks Certified Data Engineer
• Relevant AI, Machine Learning, or Generative AI certifications

Benefits

• Remote-first work environment
• Opportunity to work on enterprise-scale Microsoft Fabric and Azure data platforms
• Exposure to AI, Generative AI, Azure OpenAI, and LLM initiatives
• Opportunity to work with modern cloud and data technologies
• Collaborative, innovation-driven culture
• Exposure to diverse enterprise and consulting projects

What Success Looks Like

Within your first year, you will:

• Deliver production-grade Microsoft Fabric and Azure data platforms.
• Build scalable data architectures that support enterprise AI and LLM solutions.
• Contribute to successful implementation of RAG, vector search, and Generative AI data foundations.
• Improve data quality, governance, performance, and operational efficiency across customer environments.
• Enable scalable analytics and AI capabilities through modern engineering practices.
• Establish reusable data engineering frameworks and patterns that accelerate future Data & AI project delivery.

Application Instructions

Please share examples of data platforms, ETL/ELT pipelines, Microsoft Fabric solutions, Azure data projects, or AI/LLM data solutions you have developed, along with any relevant Microsoft, Databricks, or AI certifications.