Back
Mid-level metro data engineering role with common 4+ requirement and moderate brand yields medium competition.
Core data engineering skills are transferable, though healthcare domain experience moderately increases hiring sensitivity.
Explicit 4+ years plus mandatory Snowflake, ADF, dbt, and Python make screening highly strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and maintain scalable, reliable, and secure data ingestion pipelines into Snowflake using Snowpipe, Snowpipe Streaming, Snow Tasks, and Snow Streams.
Design and implement ELT workflows with Snowflake and dbt, integrating Azure Data Factory for orchestration and data movement.
Develop Python scripts for data ingestion, automation, and validation; monitor and optimize pipeline performance, and implement data quality, logging, and governance processes.
Minimum 4 years experience in data engineering, ETL development, or data integration.
Strong hands-on experience with Snowflake data warehousing, including Snowpipe and Snowpipe Streaming.
Experience with Azure Data Factory (ADF) for pipeline automation and orchestration.
Proficiency in Python scripting and strong SQL skills; working knowledge of dbt and PostgreSQL.
Experienced in building large-scale batch and near-real-time data ingestion pipelines with Snowflake and Azure data tools.
Skilled in ELT workflow design using dbt with version control and documentation practices.
Comfortable integrating diverse data sources (APIs, files, cloud storage) into Snowflake with automated monitoring and data quality enforcement.