Back
Mid-level Data Engineer title with common skills attracts many applicants, increasing competition.
Core data engineering skills are transferable, though fintech preference increases domain specificity.
Mandatory five years and specific cloud, ETL, and Snowflake skills enforce strict screening.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable, secure, and highly available data architectures on cloud platforms such as AWS, Azure, or Google Cloud.
Build and maintain data pipelines, ETL processes, and data warehouses to ensure smooth data flows and availability.
Ensure data quality, accuracy, and consistency across multiple data sources; write SQL queries and maintain documentation for data pipelines, data models, and database schema.
Bachelor’s degree in Science, Technology, or Engineering (any).
Minimum 5 years of experience in data engineering or related occupation.
Proficiency with cloud platforms (AWS, Azure, or Google Cloud) and tools including Python, Java, Scala, RDBMS, NoSQL, and cloud data warehousing services like Snowflake.
Work location: Alpharetta, GA and various unanticipated locations throughout the U.S.
Experienced in developing and maintaining cloud-native data architectures and pipelines at scale.
Skilled in multiple programming languages (Python, Java, Scala) and diverse database technologies (RDBMS, NoSQL, Snowflake).
Able to manage data quality and documentation rigorously across multiple data sources for analytics and reporting.