We are seeking an experienced
AI Data Engineer
with strong hands-on expertise in
Microsoft Fabric
,
Azure Data Services
, and modern data engineering practices. This role will be responsible for designing, building, and maintaining scalable data platforms that support advanced analytics, AI, and machine learning initiatives across the organization.
The ideal candidate combines deep technical knowledge with a strong understanding of data architecture, governance, and AI integration, working closely with cross-functional teams to deliver high-value data solutions.
Key Responsibilities:
Data Engineering & Architecture
Design, build, and maintain scalable data pipelines using
Microsoft Fabric
(Data Factory, Dataflows, Lakehouse, Warehouse, OneLake).
Develop robust data ingestion, transformation, and orchestration workflows leveraging
Azure Data Factory, Azure Databricks, Azure Synapse
, and
Azure Functions
.
Implement and optimize
Delta Lake
architectures for both structured and unstructured data.
Create reusable and high-quality data products to support analytics, AI, and machine learning use cases.
AI & Advanced Analytics Integration
Collaborate with
Data Scientists and ML Engineers
to operationalize AI/ML models using
Azure Machine Learning
,
Microsoft Fabric Data Science
, or
Databricks
.
Prepare, curate, and feature-engineer datasets optimized for AI and ML workloads.
Automate
MLOps
processes, including model deployment, monitoring, and lifecycle management.
Governance, Quality & Security
Implement data quality, observability, monitoring, and lineage frameworks using
Microsoft Fabric
and
Azure Purview
.
Ensure compliance with data governance, privacy, and security standards.
Manage
CI/CD pipelines
for data solutions using
Azure DevOps
or
GitHub
.
Collaboration & Stakeholder Engagement
Work closely with business analysts, product owners, and domain experts to understand requirements and translate them into scalable data solutions.
Maintain clear and up-to-date documentation of data sources, models, pipelines, and best practices.
Provide technical guidance and mentorship to junior data engineers and developers.
Required Skills & Qualifications
10+ years of experience
as a Data Engineer, AI Engineer, or in a similar role.
Strong hands-on experience with
Microsoft Fabric
, including Lakehouse, Data Engineering, Data Factory, and Data Pipelines.
Advanced expertise in
Azure Data Services
, including:
Azure Data Factory
Azure Databricks / Apache Spark
Azure Synapse Analytics / SQL Pools
Azure Storage (ADLS Gen2)
Azure Functions
Azure Machine Learning
Strong proficiency in
Python
and
SQL
for data processing and transformation.
Proven experience designing and implementing
data lakehouse architectures
and
Delta Lake pipelines
.
Solid understanding of
DevOps and MLOps
practices, including version control, testing, and automated deployments.
Experience with
data governance frameworks
, preferably using
Azure Purview
or Microsoft Fabric governance capabilities.