Description

You design, build, and optimize scalable data pipelines and platforms for enterprise operations. This role is on-site.

Responsibilities

• Design and implement ETL/ELT frameworks using distributed processing technologies for large-scale data operations.
• Develop and maintain automated data workflows using tools like Airflow, dbt, Dagster, or Luigi.
• Deploy and manage cloud-based data services on AWS, GCP, or Azure to ensure optimal data management.
• Translate ambiguous business requirements into reliable, efficient data pipeline solutions for stakeholders.
• Implement version control, CI/CD practices, and infrastructure-as-code to maintain code quality and deployment standards.

Required Skills

• 2+ years of experience in data engineering or related roles.
• Strong proficiency in SQL and Python.
• Hands-on experience with Apache Spark for data processing.
• Experience building data pipelines and ETL processes.
• Proficiency with Airflow for workflow orchestration.
• Experience with dbt for data transformation.
• Working knowledge of at least one major cloud platform: AWS, GCP, or Azure.

Preferred Skills

• Experience with Scala, Java, or other JVM languages.
• Familiarity with data warehousing concepts, dimensional modeling, and lakehouse architectures.
• Knowledge of data quality, observability, governance, and compliance standards.

Key Skills

Education

Any Graduate