Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL workflows.

• Manage large datasets and optimize data infrastructure for performance and reliability.

• Automate workflows and improve data delivery processes.

• Collaborate with Product, Analytics, and Business teams to resolve data issues.

• Ensure data integrity, governance, and security across cloud environments.

• Develop analytics solutions to generate actionable business insights.

• Lead and mentor a small team of data engineers.

• Establish coding standards, conduct code reviews, and support best practices.

• Enhance scalability and efficiency of data systems and architectures.

• Continuously improve data platforms using modern technologies and frameworks.

Qualifications:

• 6+ years of experience in Data Engineering and scalable data systems.

• Strong expertise in Python, SQL, Spark, Kafka, Airflow, and Databricks.

• Hands-on experience with AWS services such as EC2 and RDS.

• Proficient in PostgreSQL, MongoDB, and modern data modeling practices.

• Experience with REST APIs, GraphQL, SFTP, and workflow orchestration tools.

• Familiarity with SQLMesh, CI/CD pipelines, and cloud-based architectures.

• Knowledge of Streamlit, JavaScript, or TypeScript is a plus.

• Strong leadership, communication, and problem-solving abilities.

• Understanding of data governance, security, and scalable infrastructure.

• Experience with blockchain, cryptocurrency, or financial data is an added advantage.