Role : Microsoft Fabric / Azure Data Engineer

Employment Type : Full-Time

Location : Remote

Experience : 4 - 7 Years Preferred

Role Summary :

Alareeb International Technologies Private Limited is looking for a hands-on Microsoft Fabric / Azure Data Engineer to own, develop, and operate our data platform supporting IoT, Computer Vision, AI/ML, Knowledge Systems, and Business Analytics. The ideal candidate should be a strong hands-on builder who can work with heterogeneous data sources, troubleshoot complex data engineering challenges, and deliver reliable, production-ready data pipelines. This role requires practical implementation experience rather than an advisory or architecture-only background.

Key Responsibilities :

- Design, develop, and operate scalable data platforms using Microsoft Fabric, OneLake, and Lakehouse.

- Build and maintain data pipelines using Data Pipelines and Dataflows Gen2.

- Implement BronzeSilverGold Medallion Architecture for structured and unstructured data.

- Develop data ingestion and transformation pipelines for IoT, operational, image/video, and knowledge-domain data.

- Work with Azure Blob Storage / ADLS for large-scale data storage and processing.

- Develop data solutions using SQL, Python, and PySpark.

- Work with PostgreSQL and TimescaleDB for operational and time-series data.

- Build and manage IoT and time-series data engineering pipelines.

- Prepare and manage large-scale image and video datasets, including associated metadata.

- Support image vectorization, embeddings, and vector data handling for Computer Vision and AI/ML applications.

- Develop data pipelines for knowledge-domain data, document ingestion, and embeddings.

- Integrate data from external systems and applications using REST APIs and other integration methods.

- Prepare and optimize data for Power BI reporting and analytics.

- Monitor, troubleshoot, and optimize production data pipelines and data platform components.

- Ensure data pipelines are scalable, reliable, maintainable, and production-ready.

- Collaborate with AI/ML, Computer Vision, analytics, and business teams to understand data requirements and deliver appropriate data solutions.

Data Platform Scope :

The engineer will help build and operate the data foundation connecting IoT + Operational Data + Images/Video + Knowledge Data - Fabric/Blob - AI/ML + Computer Vision + Power BI. The role will involve handling both structured and unstructured data, including large-scale image/video datasets, metadata, embeddings, and vector representations.

Required Skills & Experience :

- 4 - 7 years of relevant Data Engineering experience preferred.

- Hands-on experience with Microsoft Fabric.

- Strong understanding of OneLake and Fabric Lakehouse.

- Experience with Azure Blob Storage / ADLS.

- Strong understanding of BronzeSilverGold Medallion Architecture.

- Strong SQL and Python skills.

- Hands-on experience with PySpark.

- Experience building data pipelines and Dataflows Gen2.

- Experience with PostgreSQL and/or TimescaleDB.

- Experience working with IoT and time-series data.

- Experience handling image/video datasets and metadata.

- Understanding or hands-on experience with embeddings, vectorization, and vector data.

- Experience with document ingestion and knowledge-domain data.

- Experience integrating systems using REST APIs.

- Experience preparing data for Power BI.

- Strong troubleshooting and problem-solving skills.

- Ability to independently build, deploy, monitor, and support production data pipelines.

Preferred Experience :

- Experience supporting Computer Vision data pipelines.

- Experience with AI/ML data pipelines.

- Experience working with image/video metadata and large-scale datasets.

- Practical experience implementing vector/embedding-based data solutions.

- Experience integrating heterogeneous data sources into Microsoft Fabric/Azure.

- Experience working in production environments with large and diverse datasets.

Ideal Candidate :

We are looking for a hands-on Data Engineer and builder who can take ownership of the complete data engineering lifecycle. The ideal candidate should be comfortable working directly with data, writing code, developing pipelines, troubleshooting production issues, and continuously improving the platform. Candidates whose experience is primarily limited to high-level architecture or advisory work may not be the right fit.

What the Candidate Should Provide :

Interested candidates should share :

- Updated CV :
- Examples of data platforms they have personally implemented :
- Details of projects involving :
1. Microsoft Fabric / Azure
2. IoT / Time-Series Data
3. Computer Vision datasets
4. Image/Video data pipelines
5. Vectorization / Embeddings
6. AI/ML data pipelines