Data Engineer

Job Title: Data Engineer

Location: Ghansoli, Navi Mumbai
Work Mode: 5 Days Work from Office

Experience: 7-10 Years
Employment Type: Full-Time

Job Summary

We are seeking an experienced Data Engineer with 7-10 years of hands-on experience in building scalable data platforms and data pipelines. The ideal candidate must have strong expertise in Data Engineering, SQL, Databricks, Python, and PySpark. The role involves designing, developing, and optimizing enterprise-grade data solutions to support analytics, reporting, and business intelligence initiatives.

Must-Have Skills

• Data Engineering
• SQL
• Databricks
• Python
• PySpark

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks and PySpark.
• Build robust ETL/ELT frameworks for ingesting, transforming, and processing large datasets.
• Develop optimized SQL queries, stored procedures, and data models.
• Design and implement data lakes, data warehouses, and Lakehouse architectures.
• Improve performance, scalability, and reliability of existing data pipelines.
• Collaborate with business stakeholders, data analysts, architects, and development teams to understand data requirements.
• Ensure data quality, governance, security, and compliance standards are met.
• Troubleshoot and resolve complex data processing and integration issues.
• Create and maintain technical documentation, architecture diagrams, and best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 7-10 years of experience in Data Engineering and Data Platform development.
• Strong hands-on experience with Databricks, PySpark, Python, and SQL.
• Experience in designing and optimizing large-scale data pipelines and ETL processes.
• Strong understanding of data warehousing concepts, dimensional modeling, and data architecture.
• Experience working with cloud platforms such as Azure, AWS, or GCP.
• Proficiency in performance tuning and troubleshooting Spark workloads.
• Strong analytical, problem-solving, and communication skills.