Pyspark Data Engineer

Job Summary

We are seeking an experienced Data Engineer (PySpark) to join our Data Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining large-scale data pipelines, data marts, and analytical solutions. The role requires strong expertise in Python, PySpark, SQL, Data Warehousing, and Big Data technologies, along with hands-on experience across the end-to-end Software Development Life Cycle (SDLC).

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines and data processing frameworks.
• Build and support Data Mart solutions to meet business and analytical requirements.
• Develop high-quality, maintainable, and efficient code using Python and PySpark.
• Participate in the complete Software Development Life Cycle (SDLC), including:
• Requirement Analysis
• Development
• Unit Testing
• UAT Support
• Defect Fixing
• Production Deployment
• Post-Production Support
• Perform complex data analysis and troubleshoot data-related issues.
• Debug and optimize PySpark applications for performance and reliability.
• Write and optimize complex Oracle SQL queries.
• Work with structured, semi-structured, and unstructured datasets.
• Implement data quality, validation, and monitoring processes.
• Collaborate with cross-functional teams to resolve dependencies and ensure timely project delivery.
• Follow software engineering best practices, coding standards, testing methodologies, and CI/CD processes.

Required Skills & Experience

Data Engineering & Big Data

• PySpark
• Apache Spark
• Hadoop Ecosystem
• MapReduce
• Hive
• ETL Development
• Data Pipeline Development
• Data Mart Development
• Data Warehousing

Programming

• Python
• Pandas
• Jupyter Notebook

Database Technologies

• Oracle SQL
• SQL
• NoSQL Databases
• Query Optimization
• Data Analysis

Workflow & Automation

• Apache Airflow
• Oozie
• Jenkins
• Git
• CI/CD Pipelines

Data Engineering Techniques

• Data Cleansing
• Data Linking
• Feature Engineering
• Data Imputation Techniques
• Data Validation and Quality Checks

Preferred Experience

• Banking or Financial Services domain experience.
• Experience supporting enterprise-scale data platforms.
• Exposure to production support and deployment activities.
• Experience working in Agile environments.

Desired Competencies

• Strong analytical and problem-solving skills.
• Excellent debugging and troubleshooting capabilities.
• Ability to lead technical initiatives with ownership and accountability.
• Strong collaboration and stakeholder management skills.
• Excellent verbal and written communication skills.
• Ability to communicate effectively with both technical and non-technical stakeholders.
• Ability to prioritize tasks and perform effectively in a fast-paced environment.