Back
Popular data engineering role with broad skills at a recognizable services firm, attracting moderate applicant density.
Core data engineering skills are transferable, but Prophecy and enterprise data platform requirements increase specialization.
Explicit 2-3 years requirement plus mandatory PySpark, Prophecy, and ETL skills enforce strict filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and operate scalable ETL/ELT data pipelines for batch and real-time data ingestion and transformation.
Engineer and maintain reliable, highly available data platforms including data lakes and warehouses.
Implement system integrations via APIs, streaming, and data integration tools; apply Spark/PySpark and advanced SQL for large-scale data processing and transformations, embedding data quality and security controls.
Graduate degree in Computer Science, Data Science, or related field.
2-3 years of experience in data engineering or related field.
Proficiency in Python, Apache Spark/PySpark, advanced SQL, and ETL pipeline development.
Experience with DevOps practices including CI/CD, orchestration, monitoring, and production support.
Experienced in building and deploying data pipelines with Prophecy and PySpark with strong software engineering fundamentals.
Skilled in large-scale data processing and optimization using Apache Spark and SQL in both batch and streaming contexts.
Capable of ensuring data quality, governance, and security across complex data workflows and platforms.