Hiring: Data Engineer with Cloud exposure (Py Spark + Python + SQL + Azure + Kafka)
Location: Worli Mumbai
Experience: 3+ Years
Employment Type: Full-Time
Job Overview
Key Responsibilities
Design, develop, and optimize scalable ETL and data pipelines using Py Spark and Big Data technologies.
Work on large-scale data processing using Spark and Hadoop ecosystems.
Develop and maintain robust data models, schema designs, and efficient SQL queries.
Ensure high performance, scalability, reliability, and data quality across data engineering solutions.
Build, manage, and optimize data integration workflows across multiple data sources.
Collaborate with cross-functional teams to support data ingestion, transformation, and analytics requirements.
Participate in performance tuning, monitoring, and optimization of data pipelines.
Support cloud-based data engineering initiatives on Azure or AWS platforms.
Must-Have Skills
Strong experience in Py Spark and SQL.




Hands-on experience with Big Data technologies (Spark, Hadoop).
Expertise in ETL pipeline development and optimization.
Strong understanding of data modeling and schema design.
Proficiency in Python for data engineering and data processing.
Experience working with cloud platforms such as Azure or AWS.
Good understanding of data warehousing concepts and scalable data architectures.
Good-to-Have Skills
Experience with Kafka or real-time data ingestion frameworks.
Experience in performance tuning and optimization of large-scale data pipelines.
Exposure to modern data engineering best practices and distributed data processing systems.
Preferred Profile
Solid problem-solving and analytical skills.
Ability to work in a fast-paced, collaborative environment
Excellent communication and stakeholder management skills.
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