- Design, develop, and support ETL/ELT pipelines using Python, PySpark, and Databricks

- Lead the development and optimization of large-scale data processing workflows

- Build and maintain data solutions on the AWS cloud platform

- Develop and manage streaming data pipelines using Kafka or similar frameworks

- Apply data warehousing and data modeling techniques to support analytics and reporting

- Collaborate with analytics, visualization, and business teams to deliver data-driven solutions

- Ensure data reliability, scalability, performance, and security

- Provide production support, troubleshooting, and performance tuning

- Mentor junior engineers and lead technical discussions

- Follow best practices in Agile development and CI/CD processes

Required Skills & Qualifications :

- Minimum 8+ years of overall experience in application development and production support

- At least 5+ years of hands-on experience with ETL development, Python, Databricks, and PySpark

- Strong experience with Python, Apache Spark, and Hive

- Solid understanding of data warehousing concepts and data modeling techniques

- Strong experience with AWS cloud services for data engineering solutions

- Hands-on experience with streaming frameworks such as Kafka

- Knowledge of data visualization and analytics tools such as Tableau or R

- Excellent problem-solving, analytical, and communication skills

Preferred Qualifications:
- Experience leading or mentoring data engineering teams

- Exposure to CI/CD pipelines and DevOps practices

- Experience working with large-scale, real-time data platforms

- AWS certifications or Databricks certifications