Back
Mid-level, popular data engineer in metro with broad requirements; specialized Spark/Scala narrows the applicant pool.
Data engineering skills are transferable, but AEP and Spark/Scala specialization moderately limit cross-industry fit.
Multiple mandatory technical requirements (6+ years, GCP, Spark, Scala, Docker/Kubernetes) make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and maintain scalable data pipelines leveraging cloud technologies and machine learning.
Work closely with product development to resolve data-related issues and ensure data quality with checkpoints for QA.
Develop and train machine learning models and create infrastructure tooling and horizontal frameworks.
5 to 9 years of experience with relevant data engineering technologies.
Bachelor's or Master's degree in Computer Science or related technical field.
6+ years experience with Google Cloud Platform, Spark, and Scala mandatory.
Strong experience in Python, SQL, RDBMS (SQL Server preferred), AWS, containerization tools (Docker, Kubernetes).
Experienced in cloud environments including Google Cloud Platform and AWS with hands-on knowledge of services like Redshift, EMR, and Glue.
Skilled in multiple programming and scripting languages including Python, Shell, C#, Java, and proficient in SQL optimization.
Capable of integrating big data tools (Hadoop, Hive, Spark) and message queuing/stream processing for scalable data architectures.