Back
Popular mid-level data-engineer role with broad stack and metro location increases competition.
Core data engineering skills (Java, Spark, cloud) are highly transferable across industries.
Explicit 3+ years and mandatory Java, Spark, Hadoop, and cloud requirements increase filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and optimize scalable batch and real-time data pipelines, transitioning legacy workloads to cloud.
Collaborate with architects and senior leaders to support Data Cloud roadmap execution, ensuring system reliability and operational excellence.
Write high-quality code, participate in code reviews, and implement CI/CD, automated testing, and infrastructure as code within agile teams.
3+ years of software or data engineering experience delivering production-grade data solutions.
Proficient in Java with experience building scalable, high-performance data processing applications.
Experience with big data technologies including Hadoop and Apache Spark.
Experience with cloud data infrastructure on GCP or AWS and knowledge of microservices and containerization technologies.
Operates well in cross-functional, agile team environments with emphasis on execution and alignment to project timelines.
Strong technical troubleshooting skills to optimize data pipelines, cloud costs, and query performance independently.
Experienced in maintaining engineering standards including code quality, documentation, and testing in fast-paced environments.