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Senior Data Engineer (AI & LLM Solutions)
Location: Remote(Pakistan, Mexico, India, Morocco)
Department: Digital Solutions / Data Engineering & AI
Reports To: Technical Lead / Director
Job Type: Full-time
About AIM
Architecture in Motion Inc. (AIM) is a Canadian technology consulting firm that supports organizations across public and private sectors with software engineering, cloud platforms, API integration, data engineering, and enterprise technology solutions.
We specialize in delivering scalable, secure, and modern digital solutions leveraging Microsoft technologies, helping our clients drive operational efficiency, data modernization, and digital transformation.
Role Overview
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, and 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.
Required 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
Core Competencies
Strong analytical and problem-solving skills
Ability to design and implement scalable data solutions
Strong understanding of enterprise data architecture
Ability to work independently in a remote and cross-functional environment
Strong communication and stakeholder management skills
Ability to mentor engineers and provide technical leadership
Strong focus on security, quality, performance, and reliability
Ability to translate business requirements into technical solutions
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
What We Offer
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.