Join a high-performance team as a Senior Data Engineer, responsible for designing and maintaining scalable data pipelines.

About the Company

Magus Infotech India Pvt. Ltd. is a fast-growing IT firm focused on delivering innovative technology solutions. We take pride in fostering a collaborative work environment that encourages creativity, agility, and solutions-oriented thinking. Our company values continuous development and aims to provide exceptional career growth opportunities to its employees.

Role Overview

We are seeking a highly motivated and independent Senior Data Engineer to become an integral part of our high-performance team. This is an exciting opportunity for someone with at least a year of hands-on experience in data engineering who is capable of designing, developing, and maintaining scalable data pipelines. This role offers the potential to work on modern data platforms and contribute to critical data solutions for the business.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines to ensure efficient data flow.
• Build and optimize data models, data warehouses, and data integration solutions to support analytical needs.
• Extract, transform, and load data from multiple structured and unstructured sources, maintaining the quality and integrity of the data.
• Collaborate with cross-functional teams, including Data Analysts, BI Developers, and Software Engineers, to facilitate data-driven decision making.
• Troubleshoot data issues and optimize existing workflows for improved efficiency.
• Prepare comprehensive technical documentation and support production deployments.

Tech Stack

• Languages: SQL, Python
• Tools: ETL tools, data pipeline development tools, version control tools (Git)
• Cloud Platforms: AWS, Azure, Google Cloud (preferable)
• Technologies: Apache Spark, Databricks, Airflow (familiarity is advantageous)

If you are passionate about building scalable data solutions and thrive in a challenging environment, we would love to hear from you!

Requirements

• Minimum of 1 year of hands-on experience in Data Engineering.
• Strong knowledge of SQL and relational databases.
• Proficient in Python for data processing and automation.
• Experience with ETL tools and data pipeline development.
• Understanding of Data Warehousing concepts and dimensional modeling.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud is preferred.
• Familiarity with Apache Spark, Databricks, Airflow, or similar technologies is an advantage.
• Knowledge of version control tools such as Git.
• Self-driven with strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Willingness to learn new technologies in a fast-paced environment.

Benefits

• Cell phone reimbursement.
• Flexible schedule.