Description

You will lead the design and optimization of large-scale data architectures and engineering workflows.

Responsibilities

• Design, develop, and optimize large-scale ETL/ELT pipelines for structured and unstructured data.
• Implement data lake solutions using Apache Iceberg on cloud-native platforms.
• Manage data governance, version control, schema evolution, and ACID compliance.
• Collaborate with Data Scientists, Architects, and Product teams to meet business requirements.
• Mentor junior engineers and lead technical teams through complex data implementations.

Required Skills

• 10+ years of hands-on experience in ETL, SQL, Data Lakes, and Hadoop.
• Deep expertise in Apache Iceberg and data lake table formats.
• Strong proficiency in Python and Shell scripting.
• Experience with cloud platforms including AWS, Azure, or GCP.
• Proven ability to design scalable data pipelines and data lake architecture.
• Knowledge of data orchestration tools like Airflow.
• Understanding of data governance, metadata management, and data quality frameworks.
• Familiarity with banking data domains such as customer, transaction, credit, and risk.
• Bachelor’s or master’s degree in Computer Science, Data Science, or Data Analytics.

Key Skills

Education

Any Gradute