Back
High due to Tier-1 brand, metro location, popular data engineering role, and mid-level seniority.
Low because Kubernetes, Spark, Python, and data engineering skills are broadly transferable across industries.
High because many mandatory production data, Kubernetes, Spark, monitoring, and tooling skills are specified.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Manage and operate production Kubernetes clusters ensuring high availability, performance, and reliability.
Build, maintain, and enhance large-scale ETL data pipelines and monitoring dashboards (Grafana/Power BI).
Support analytics and AI/ML use cases through data analysis, feature engineering, and collaborating with stakeholders.
Hands-on experience operating Kubernetes in production environments.
Experience building and maintaining ETL pipelines and working with big data tools like Apache Spark.
Proficiency in Python for data analysis and feature engineering.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced data engineer with strong Kubernetes cluster management skills focused on reliability and observability.
Able to support AI/ML workflows through data processing, analysis, and model deployment collaboration.
Capable of interfacing with internal and external stakeholders to deliver scalable data solutions in a production R&D setting.