Description

Job Responsibilities include:

Design, build, and manage scalable ETL/ELT data pipelines for efficient data ingestion and transformation.

Monitor data workflows and systems to detect failures, troubleshoot issues, and ensure SLA adherence.

Implement data quality checks, validation, and governance policies to maintain accuracy and consistency.

Optimize data platforms (AWS/Azure/GCP, data lakes, and warehouses) for performance, scalability, and cost efficiency.

Automate processes and support CI/CD practices for continuous improvement in DataOps workflows.

Collaborate with cross-functional teams to translate business needs into data solutions and support analytics and reporting.

Required Qualifications:

Bachelor’s degree in computer science, Engineering, Data Science, or a related field.

8–10 years of experience in Data Engineering or DataOps roles.

Strong proficiency in Python with hands-on experience building and managing ETL/ELT pipelines.

Experience working with cloud platforms (AWS/Azure/GCP) and implementing DataOps practices for scalable, high-performance data systems

Key Skills

Education

Any Graduate