Data Engineer - PySpark

We are seeking a Data Engineer with expertise in Data Architecture, Data Strategy, and Roadmap for large and complex organizations. The ideal candidate will implement large-scale end-to-end Data Management and Analytics solutions and transform traditional Data Warehousing approaches to Big Data-based methods.

Key Responsibilities:

• Manage risks and ensure data security.
• Apply DW Dimensional modeling techniques, including Star and Snowflake schemas, slowly changing dimensions, and dimensional hierarchies.
• Work with cloud-native principles, designs, and deployments.
• Enhance Continuous Integration (CI) and Continuous Development (CD) environments.
• Focus on Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival.
• Define workload migration strategies using appropriate tools.
• Drive delivery in a matrixed environment, collaborating with various internal IT partners.
• Independently manage tasks in a fast-paced and changing environment with short deadlines.

Qualifications:

• Strong problem-solving, influencing, communication, and presentation skills.
• Experience with data processing frameworks and platforms (Hadoop, Presto, Tez, Hive, Spark, etc.).
• Hands-on experience with big data platforms and related programming languages (Linux, Python, PySpark, GIT, Jenkins).

This role requires a self-starter who can manage multiple tasks and projects simultaneously while delivering results effectively.