Description

Key Skills: Snowflake, SQL, Python, Azure Data Factory (ADF), Data Warehousing, Dimensional Modelling, ELT/ETL, Data Pipelines, Git, CI/CD, APIs, DBT, Airflow, Spark, Databricks, Kafka, Cloud Platforms

Roles & Responsibilities

• Design, develop, and optimize scalable Snowflake data models, schemas, and data pipelines.
• Build and maintain Azure Data Factory (ADF) pipelines for data ingestion and workflow orchestration.
• Develop efficient ELT/ETL pipelines for batch and streaming data processing.
• Write complex SQL and Python scripts for data transformation, processing, and automation.
• Optimize Snowflake workloads for performance and cost efficiency.
• Implement data quality checks, monitoring, observability, governance, and security controls.
• Design and consume APIs and support data contracts for reliable data integration.
• Use Git and CI/CD practices to manage and deploy data engineering workloads.
• Collaborate with analytics, business, and cross-functional teams to deliver scalable data solutions.
• Troubleshoot pipeline, data quality, and performance issues and drive continuous improvements.

Experience Required

• 5-9 years of experience in Data Engineering.
• Strong hands-on experience with Snowflake, SQL, Python, and ADF.
• Strong understanding of data warehousing and dimensional modelling.
• Experience developing ELT/ETL and data ingestion pipelines with orchestration.
• Experience with Git, CI/CD, data quality, monitoring, and observability.
• Experience with APIs, data integration, and data contracts.
• Exposure to Azure, AWS, or GCP cloud platforms.
• Good to have experience with DBT, Airflow, Dagster, Fivetran, Spark, Databricks, or Kafka.
• Knowledge of data testing frameworks such as Great Expectations or Soda is an advantage.
• Exposure to Terraform, Helm, Kubernetes, RBAC, catalogs, and data lineage is desirable.
• Strong communication, problem-solving, collaboration, and ownership skills.

Education: Any Post Graduation, Any Graduation

Key Skills

Education

Any Graduate