- Design, develop, and maintain scalable and reliable data pipelines and data platforms.

- Develop and optimize data transformations and workflows using Snowflake, DBT, SQL, and PySpark.

- Build and manage data pipelines and orchestration workflows using Apache Airflow.

- Work with AWS and/or Azure cloud services for data processing, storage, and deployment.

- Develop efficient ETL/ELT processes and ensure data quality, accuracy, and reliability.

- Optimize SQL queries, data models, and pipeline performance.

- Collaborate with Data Scientists, Analysts, Architects, and business teams to understand data requirements.

- Implement data engineering best practices around monitoring, testing, security, and governance.

- Troubleshoot data pipeline and production issues and provide timely resolutions.

Required Skills :

- Strong hands-on experience with Snowflake.

- Proficiency in DBT and SQL.

- Strong experience with PySpark.

- Hands-on experience with Apache Airflow.

- Experience with AWS and/or Azure cloud platforms.

- Strong understanding of data engineering, ETL/ELT, data modeling, and data warehousing concepts.

- Good problem-solving and analytical skills.

- Strong communication and collaboration skills.

Preferred Candidate Profile :

- Experience building enterprise-scale data platforms and pipelines.

- Experience with cloud-based data engineering architectures.

- Strong understanding of data quality, governance, and pipeline monitoring.

- Ability to work effectively in a fast-paced, collaborative environment.

- Experience working with cross-functional technology and business teams.

Perks & Benefits :

- Competitive compensation package.

- Opportunity to work on large-scale cloud and data engineering projects.

- Exposure to modern data technologies and platforms.

- Collaborative and learning-oriented work environment.