Data Architect - Microsoft Azure Data Services, DataLake, Databricks

We are looking for a seasoned Data Architect with over 10 years of experience in designing, developing, and managing modern data platforms, pipelines, and cloud-based analytics solutions. The ideal candidate will have deep expertise in Azure Data Services, large-scale data processing, data warehousing, and ETL/ELT frameworks. This role demands hands-on experience in building scalable, secure, and high-performance data architectures that support enterprise analytics, reporting, AI, and business intelligence initiatives. The position offers a mostly remote work model with occasional office presence and is based in Pakistan.

Key Responsibilities

- Design, develop, and maintain scalable data platforms and pipelines on Microsoft Azure.
- Build and optimize batch and real-time data ingestion frameworks from diverse structured and unstructured sources.
- Architect and implement data lake, data warehouse, and lakehouse solutions to support analytics and reporting needs.
- Develop and manage ETL/ELT processes using cloud-native data engineering best practices.
- Implement data transformation, cleansing, validation, and quality frameworks to ensure data accuracy and reliability.
- Collaborate closely with business stakeholders, data analysts, data scientists, and application teams to understand requirements and deliver scalable solutions.
- Optimize data storage, processing, and query performance across enterprise data platforms.
- Enforce security, governance, monitoring, and compliance standards within Azure environments.
- Support integration of data platforms with AI/ML, business intelligence, and enterprise applications.
- Participate in architecture and code reviews, troubleshooting, and provide technical mentoring.
- Ensure high availability, scalability, and operational excellence of data platforms and pipelines.

Required Qualifications

- Over 10 years of experience in Data Engineering, Data Warehousing, and Enterprise Data Platform development.
- Strong hands-on expertise with Microsoft Azure Data Services.
- Proficiency in Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), and Azure SQL Database.
- Extensive experience building and managing large-scale ETL/ELT pipelines and data integration solutions.
- Advanced skills in SQL, query optimization, and database performance tuning.
- Hands-on experience with PySpark, Apache Spark, and distributed data processing frameworks.
- Programming proficiency in Python, Scala, or Java.
- Solid understanding of dimensional modeling, data warehousing concepts, and modern lakehouse architectures.
- Experience working with structured, semi-structured, and unstructured data.
- Strong knowledge of data governance, data quality, metadata management, and security best practices.
- Familiarity with REST APIs, data integration patterns, and enterprise system connectivity.
- Experience with Git, CI/CD pipelines, and DevOps methodologies.
- Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications and Benefits

- Experience with Microsoft Fabric, OneLake, Dataflows, and Fabric Data Engineering workloads.
- Hands-on experience with Databricks, Delta Lake, and lakehouse implementations.
- Knowledge of real-time streaming technologies such as Azure Event Hubs, Apache Kafka, or Azure Stream Analytics.
- Experience supporting AI/ML and advanced analytics workloads through enterprise data platforms.
- Familiarity with Power BI datasets, semantic models, and enterprise reporting architectures.
- Experience with data governance tools like Microsoft Purview.
- Microsoft Azure Data Engineering certifications are highly desirable.
- Experience working in Agile/Scrum environments.
- Exposure to MLOps and DataOps practices.
- Knowledge of containerization technologies such as Docker and Kubernetes is a plus.

This role offers an excellent opportunity to work on cutting-edge cloud data engineering projects within a dynamic and collaborative environment. If you are passionate about architecting scalable data solutions and driving enterprise analytics, we encourage you to apply.