Python/ETL Developer

Wissen Infotech

Bengaluru

On-site

INR 3,200,000 - 5,200,000

Full time

14 days+
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Job summary

Wissen Infotech is seeking a Python/ETL Developer to design and maintain scalable data pipelines for enterprise-scale product ecosystems. The role emphasizes building robust Python/PySpark applications and implementing modern ETL frameworks to deliver reliable data solutions for financial services applications.

You will work with Airflow, DBT, SQL, and various data technologies to ensure data quality and operational excellence, contributing to production-grade data platforms across systems.

Qualifications

  • 5+ years of Python development in enterprise-grade data engineering
  • 4+ years PySpark experience in distributed data processing
  • 5+ years building batch and real-time data pipelines
  • Experience designing scalable, fault-tolerant data platforms
  • 3+ years of workflow orchestration with Airflow
  • DBT for data transformation and analytics engineering
  • Strong SQL and data modeling fundamentals
  • REST APIs, shell scripting, and CI/CD for deployment
  • Experience with Trino/Snowflake or equivalent engines
  • Familiarity with AI-assisted development tools

Responsibilities

  • Design, develop, and optimize scalable batch and real-time data pipelines for high-volume workloads
  • Build robust Python and PySpark applications to support data engineering and analytics use cases
  • Develop and maintain ETL frameworks using Spark, DBT, and Airflow
  • Implement data governance, lineage, security, and compliance across data layers
  • Design scalable system architectures ensuring reliability and performance of data platforms
  • Develop and consume RESTful APIs to integrate data platforms with other systems
  • Build and maintain CI/CD pipelines for automated testing and deployment
  • Collaborate with architects, product teams, and stakeholders to deliver high-quality solutions
  • Leverage AI-assisted tools to boost engineering productivity and feature delivery
  • Troubleshoot production issues and optimize query performance for stability

Skills

Python
PySpark
ETL Pipelines
System Design
Airflow
DBT
SQL
CI/CD
Query Engines
AI Code Assistants

Education

BE/BTech/ME/MTech in CS/IT/Engineering

Tools

Kubernetes
Docker
GitHub Copilot
Autosys

Job description

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.

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