Description

You will architect and own the long-term vision for a scalable data platform, focusing on Data Ops practices and automated data provisioning.

Responsibilities

• Design and implement scalable, repeatable data flow schemes in Hadoop or cloud environments to eliminate manual bottlenecks.
• Establish Data Ops practices by automating data provisioning, testing, and monitoring to shorten development cycles.
• Build mature data pipelines with strict governance, CI/CD integration, and comprehensive test coverage.
• Evaluate and recommend tools and technology strategies for analytics platforms in collaboration with Enterprise Architecture.

Required Skills

• 5+ years of experience with ETL frameworks such as Airflow, Oozie, or Jenkins.
• Strong proficiency in Python, PySpark, and Unix scripting for data engineering tasks.
• Expertise in SQL query languages, including No-SQL, Hive, and SparkSQL.
• Experience designing data management systems in Hadoop or cloud environments.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or equivalent.

Preferred Skills

• Experience collaborating with Enterprise Architecture teams on technology strategy.

Key Skills

Education

Bachelor or Master's degree in Computer Science, Information Systems or equivalent field