Oracle + PySpark Data Engineer
- PradeepIT Consulting Services Pvt Ltd
- Remote — India
- Full Time
- Data Science, Developer
Job Description: Experiance:5 to 7 YearsWe 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 improveKnown 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 standards and overall data processing and analysis performance. Documentation: Create and maintain comprehensive documentation for data models, ETL processes, and codebase Originally posted on Himalayas