Description

job responsibilities include:

Design, build, and operate large‑scale data pipelines using Azure Synapse Analytics (Spark pools) and Azure Data Factory (ADF).

Develop and optimize PySpark code, including DataFrames, joins, aggregations, window functions, partitioning strategies, caching, and handling data skew.

Build and maintain ETL/ELT pipelines supporting analytics, reporting, and AI/ML workloads in production.

Implement and maintain CI/CD pipelines for data and analytics solutions.

Ensure data reliability, performance tuning, scalability, and operational stability across Azure-based platforms.

Desired Qualifications:

Bachelor’s Degree in Computer Science, Engineering, Data Science, or a related field.

8–10 years of experience in data engineering, analytics engineering, or AI/ML engineering roles.

Strong hands‑on experience with Microsoft Azure, including Azure Synapse Analytics, Azure Data Factory, and Azure Storage.

Advanced proficiency in PySpark for large‑scale data processing.

Solid experience with SQL and data modeling.

Working knowledge of C# / Core .NET technologies.

Nice‑to‑have experience with:

Azure Data Explorer (Kusto)

Telemetry or large‑scale data ingestion platforms

Azure ML Studio for data preparation and ML pipeline integration

Enterprise‑scale or Microsoft‑scale environments

Key Skills

Education

Any Graduate