About The Role

We are looking for a motivated and detail-oriented Data Engineer with 3–4 years of experience in data engineering and analytics solutions. The ideal candidate should have hands-on experience with Microsoft Fabric, robust PySpark skills, and a foundational understanding of Databricks. The candidate should be eager to learn, adaptable to current technologies, and passionate about building scalable data solutions.

Key Responsibilities

Design, develop, and maintain data pipelines using Microsoft Fabric.
Build and optimize ETL/ELT processes for ingesting, transforming, and loading data from multiple sources.
Develop and maintain data transformation workflows using PySpark.
Work with Lakehouse, Data Warehouse, and Data Factory components within Microsoft Fabric.
Collaborate with business stakeholders, analysts, and data teams to understand data requirements.
Ensure data quality, consistency, and reliability across data platforms.
Monitor and troubleshoot data pipeline performance and resolve issues proactively.




Support data modeling and reporting requirements for analytics and business intelligence initiatives.
Participate in code reviews, testing, and deployment activities.
Stay updated with emerging technologies and best practices in data engineering.

Required Skills

3–4 years of experience in Data Engineering or related roles.
Hands-on experience with Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, Notebooks, etc.).
Robust proficiency in PySpark for data processing and transformation.
Good understanding of ETL/ELT concepts and data pipeline development.
Experience working with SQL and relational databases.
Basic understanding of Databricks and Spark ecosystem.
Familiarity with data lakes and modern cloud-based data architectures.
Knowledge of data quality, performance tuning, and optimization techniques.
Experience with version control tools such as Git.

Preferred Skills

Exposure to Azure Data Services.
Understanding of Delta Lake concepts.

📌 Data Engineer Mumbai
🏢 Noventiq India
📍 Mumbai