Description

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines for data ingestion, transformation, and integration.
• Work extensively with Databricks for data processing, transformation, and analytics.
• Develop and maintain data workflows using Python and SQL.
• Integrate data from multiple sources, including Azure databases and Oracle databases.
• Write optimized queries and implement efficient data transformation logic.
• Perform data cleansing, validation, and quality checks to ensure accuracy and consistency.
• Troubleshoot data pipeline failures and resolve performance and data processing issues.
• Collaborate with business analysts, data architects, and other engineering teams to understand data requirements.
• Follow best practices for data security, governance, performance optimization, and documentation.
• Support data solutions involving AI or machine learning where applicable.

Required Skills and Qualifications:

• 5–7 years of experience in data engineering or data development.
• Strong hands-on experience with Databricks.
• Experience working with Azure database technologies.
• Strong experience with Oracle Database and SQL.
• Proficiency in Python programming for data processing and automation.
• Experience with ETL/ELT processes, data integration, and data transformation.
• Strong analytical, troubleshooting, and problem-solving skills.
• Good communication and collaboration skills.

Preferred Skills:

• Exposure to AI, machine learning, or AI-enabled data solutions.
• Experience with Spark, PySpark, Delta Lake, or Azure data services.
• Experience optimizing data pipelines and processing large datasets

Key Skills

Education

Bachelor's degree