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Protocol Intelligence
Data-driven signals on your job's competitivenessGlobal brand, metro location, and a mid-level popular data-engineer role increase competition.
Core data engineering skills transfer well, but Azure- and OpenShift-specific requirements moderately limit portability.
Explicit 6–8 years plus mandatory Azure, PySpark, Databricks, OpenShift and CI/CD requirements create high strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and optimize ETL/ELT data pipelines using Python and PySpark in Azure Databricks and Azure Data Factory.
Manage and monitor data ingestion, pipeline health, and data quality using tools like Grafana.
Implement CI/CD pipelines via GitHub Actions for automated testing, build, and deployment on OpenShift with Helm.
Minimum Requirements
6–8 years of relevant experience in data engineering.
Strong proficiency in Python and PySpark for data processing.
Hands-on experience with Azure data services including Azure Databricks, Azure Data Factory, Azure SQL Server, and Azure Key Vault.
Experience with OpenShift and Helm for container orchestration and deployment.
Ideal Candidate Profile
Experienced in developing complex SQL queries with optimization and performance tuning skills.
Skilled in setting up monitoring dashboards and observability solutions like Grafana for data pipelines.
Familiarity with DevOps practices especially CI/CD automation using GitHub Actions and containerized environments (OpenShift/Kubernetes).