Description

Key Responsibilities
 

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
   
• Lead or support the migration and modernization of existing data workflows across GCP, AWS, or Azure environments.
   
• Build efficient systems for data ingestion, transformation, and delivery across platforms.
   
• Collaborate with engineering, product, and analytics teams to ensure data accessibility and integrity.
   
• Implement and monitor data governance, data quality, and performance standards.
   
• Optimize cloud resources for performance and cost efficiency.
   
• Continuously evaluate and integrate new tools and technologies to enhance pipeline performance.
   

Required Skills & Experience
 

• 6+ years of hands-on experience as a Data Engineer.
   
• Strong proficiency in SQL, Python, and data transformation frameworks.
   
• Proven experience with at least one major cloud platform: GCP, AWS, or Azure.
            GCP: BigQuery, Dataform, Dataflow, Pub/Sub, Cloud Storage
            AWS: Redshift, Glue, S3, Lambda, EMR
           Azure: Azure Data Factory, Synapse Analytics, Data Lake
   
• Strong understanding of ETL/ELT processes, data modeling, and data warehouse architectures.
   
• Experience with version control (Git) and CI/CD pipelines for data workflows.
   
• Solid understanding of data quality, observability, and reliability practices.
   

Preferred Qualifications
 

• Experience working in multi-cloud or cloud migration/modernization projects.
   
• Familiarity with orchestration tools such as Airflow, dbt, Dataform, or similar.
   
• Experience with streaming data and event-driven architectures.
   
• Strong analytical, problem-solving, and communication skills.

Key Skills

Education

Any Graduate