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).

The candidate should possess a strong analytical mindset, excellent problem-solving capabilities, and experience working with banking and financial services data environments. 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 effective 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

Educational Qualification

Bachelor's Degree in Computer Science, Information Technology, Engineering, or equivalent discipline.

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.

Technical Environment The selected candidate will be working extensively with:

Python

Spark (PySpark)

Hadoop

Jupyter Notebook

Oracle SQL

NoSQL Databases

Git

Jenkins

Airflow

Oozie

Data Warehousing Technologies

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.

Nice to Have

Experience with large-scale distributed data processing systems.

Knowledge of cloud-based data platforms.

Exposure to DevOps and DataOps practices.

Experience with data governance and regulatory compliance frameworks.

Interested candidates are encouraged to apply through the career portal with an updated resume.

📌 Data Engineer (Bengaluru)
🏢 Synechron
📍 Bengaluru