Description :
Primary Responsibilities
- Establish technical designs to meet requirements aligned with architectural and data standards
- Optimize ETL / data pipelines balancing performance, functionality, and operational requirements
- Fine-tune and optimize queries using Snowflake platform and database techniques
- Manage data ingestion, transformation, processing, and orchestration of pipelines
- Develop and maintain API, ETL Pipeline, and CI / CD integration processes
- Assist with technical solution discovery to ensure feasibility
- Set up and manage CI / CD pipelines and develop automated tests
- Conduct peer reviews for quality, consistency, and rigor for production-level solutions
- Promote best practices for code management, automated testing, and deployments
- Create design and development documentation based on standards
- Actively contribute to Data Engineering community and define leading practices and frameworks
Qualifications
Required
Bachelor's degree in computer science, engineering, or similar quantitative field5+ years of relevant experience developing backend, integration, data pipelining, and infrastructureStrong expertise in Python, PySpark, and SnowparkProven experience with Snowflake and AWS cloud platformsExperience with Informatica / IICS for data integrationExpertise in database optimization and performance improvementExperience with data warehousing and writing efficient SQL queriesUnderstanding of data structures and algorithmsPreferred
Knowledge of DevOps best practices and associated tools :o Containers and containerization technologies (Kubernetes, Argo, Red Hat OpenShift)
o Infrastructure as code (Terraform)
o CI / CD Pipelines (JFrog Artifactory)
o Scripting and automation (Python, GitHub, GitHub actions)