Oracle + PySpark Data Engineer

Job Description:

Experiance:5 to 7 Years

We are seeking a highly skilled and motivated Oracle + PySpark Data Engineer/Analyst to join our team. The ideal candidate will be responsible for leveraging the Oracle database and PySpark to manage, transform, and analyze data to support our business's decision-making processes. This role will play a crucial part in maintaining data integrity, optimizing data processes, and enabling data-driven insights.

Key Responsibilities:

1. Data Integration: Integrate data from various sources into Oracle databases and design PySpark data pipelines to enable data transformation and analytics.

2. Data Transformation: Develop and maintain data transformation workflows

using PySpark to clean, enrich, and structure data for analytical purposes.

3. Data Modeling: Create and maintain data models within Oracle databases,

ensuring data is structured and indexed for optimal query performance.

4. Query Optimization: Write complex SQL queries and PySpark transformations for efficient data retrieval and processing.

5. Data Analysis: Collaborate with data analysts and business teams to provide insights through data analysis and reporting.

6. Data Quality: Implement data quality checks, error handling, and validation

processes to ensure data accuracy and reliability.

7. Performance Tuning: Optimize Oracle database and PySpark jobs to improve

Known Tools

• Proven experience in working with Oracle databases and PySpark.

Strong proficiency in SQL, PL/SQL, Python, and PySpark.

• Familiarity with Oracle database administration, data warehousing, and ETL concepts.
• Understanding of big data technologies and distributed computing principles.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork abilities.
• Knowledge of data security and compliance standardsand overall data processing and analysis performance.
• Documentation: Create and maintain comprehensive documentation for data

models, ETL processes, and codebase

Originally posted on Himalayas