Python/ETL Developer

Job Summary

We are hiring a Python/ETL Developer to build and maintain high-performance data engineering platforms for enterprise-scale product ecosystems. The role focuses on designing scalable data pipelines, implementing modern ETL frameworks, and delivering reliable data solutions for mission-critical financial services applications.

Must Have Skills

• Python Development (5+ years of hands-on experience in enterprise-grade applications and data engineering solutions)

• PySpark Apache Spark (4+ years in distributed data processing and large-scale data transformation)

• ETL/Data Engineering/Data Pipeline Development (5+ years building batch and real-time data processing pipelines)

• System Design High-Volume Processing (experience designing scalable and fault-tolerant data platforms)

• Apache Airflow (3+ years in workflow orchestration, scheduling, and monitoring)

• DBT (Data Build Tool) for data transformation, modeling, and analytics engineering

• SQL, RDBMS OLTP Systems (strong expertise in query optimization, database fundamentals, and data modeling)

• REST APIs, Shell Scripting, and CI/CD implementation for automated deployment and operational excellence

• Query Engines such as Trino, Snowflake, or equivalent distributed data technologies

• AI-Powered Developer Assistants such as GitHub Copilot, Claude, Qwen, or equivalent AI code generation tools

  Good to Have

• Autosys job scheduling and enterprise workload automation

• AI/ML, Generative AI, and RAG (Retrieval-Augmented Generation) concepts

• Big Data ecosystem technologies and distributed computing platforms

• Data Modeling for enterprise-scale analytics and operational systems

• Messaging Queue technologies (Kafka, RabbitMQ, MQ Series, or equivalent)

• DevOps practices with Kubernetes (K8s), Docker, and cloud-native deployments

• Unix/Linux administration and scripting experience

• Banking domain expertise with AML (Anti-Money Laundering) or Capital Markets project

  Professional Attributes Qualifications

• Education: BE/BTech/ME/MTech in Computer Science, Information Technology, Engineering, or related discipline

• Leadership: Experience mentoring junior developers and contributing to technical decision-making

• Ownership: Proven ability to drive end-to-end delivery of data engineering solutions from design through production deployment

• Problem Solving: Strong analytical mindset with experience troubleshooting complex distributed systems

• Quality Focus: Commitment to coding standards, performance optimization, testing, and operational excellence

• Communication: Strong oral and written communication skills with the ability to collaborate across global teams

• Collaboration: Excellent stakeholder management skills and a strong team-player attitude

Key Responsibilities

• Design, develop, and optimize scalable batch and real-time data pipelines capable of handling high-volume data workloads
• Build robust Python and PySpark applications to support enterprise data engineering and analytics use cases
• Develop and maintain ETL frameworks using Apache Spark, DBT, and Airflow for efficient data processing
• Implement data governance, lineage, security, and compliance standards across multiple data layers
• Design scalable system architectures and ensure reliability, availability, and performance of data platforms
• Develop and consume RESTful APIs to integrate data platforms with upstream and downstream systems
• Build and maintain CI/CD pipelines to automate testing, deployment, and operational workflows
• Collaborate closely with architects, product teams, and business stakeholders to deliver high-quality solutions
• Leverage AI-assisted development tools to improve engineering productivity and accelerate feature delivery
• Troubleshoot production issues, optimize query performance, and ensure operational stability of data system.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.