Ai Ml Engineer

Infosys; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infosys seeks an AI/ML ETL Engineer for Telecom OSS & Data Analytics with 5–9 years of experience. You will design and maintain scalable ETL/ELT pipelines using Python and Apache Airflow, handling telecom OSS data to support AI/ML initiatives and analytics.

You will build data ingestion workflows, ensure data quality, collaborate with data scientists and network teams, and document data structures. This role requires strong SQL, data warehousing exposure, and a hands-on approach to optimizing

Qualifications

• 5–9 years of experience in Data Engineering, ETL Development, or Telecom Analytics.
• Strong experience in Python for data processing and automation.
• Hands-on expertise in Apache Airflow for workflow orchestration.
• Good understanding of Telecom OSS/BSS ecosystems.
• Experience in designing and developing ETL/ELT pipelines.
• Knowledge of SQL and database technologies (Oracle, PostgreSQL, MySQL, SQL Server, etc.).
• Experience with data warehousing and big data concepts.
• Understanding of AI/ML data preparation, feature engineering, and model support workflows.
• Strong analytical, debugging, and problem-solving skills.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for Telecom OSS data.
• Build and optimize data ingestion, transformation, and integration workflows using Python and Apache Airflow.
• Develop data engineering solutions to support AI/ML models and advanced analytics use cases.
• Process and analyze large volumes of telecom network, performance, fault, and operational data.
• Integrate data from OSS systems, databases, APIs, and external data sources.
• Implement data quality, validation, monitoring, and governance frameworks.
• Collaborate with Data Scientists, AI/ML Engineers, Network Operations, and Business teams.
• Automate data workflows and orchestration processes for improved efficiency.
• Troubleshoot and optimize ETL jobs for performance and reliability.
• Create technical documentation, data dictionaries, and workflow designs.

Skills

ETL Development

Python

Apache Airflow

Data Analytics

Telecom OSS data

SQL

Data Warehousing

Problem Solving

Team Collaboration

Documentation

Tools

Apache Airflow

Oracle

PostgreSQL

MySQL

Job description

Job Description: AI/ML ETL Engineer (Telecom OSS & Data Analytics)

Position: AI/ML ETL Engineer Telecom OSS Experience: 5-9 Years

Job Summary

We are seeking a highly skilled AI/ML ETL Engineer with 59 years of experience in Telecom OSS, Data Engineering, and Analytics. The ideal candidate should have strong expertise in ETL development, Apache Airflow, Python, and large-scale data processing. Experience working with telecom network and OSS data to support AI/ML and analytics initiatives is highly preferred.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for Telecom OSS data.
• Build and optimize data ingestion, transformation, and integration workflows using Python and Apache Airflow.
• Develop data engineering solutions to support AI/ML models and advanced analytics use cases.
• Process and analyze large volumes of telecom network, performance, fault, and operational data.
• Integrate data from OSS systems, databases, APIs, and external data sources.
• Implement data quality, validation, monitoring, and governance frameworks.
• Collaborate with Data Scientists, AI/ML Engineers, Network Operations, and Business teams.
• Automate data workflows and orchestration processes for improved efficiency.
• Troubleshoot and optimize ETL jobs for performance and reliability.
• Create technical documentation, data dictionaries, and workflow designs.

Required Skills

• 5–9 years of experience in Data Engineering, ETL Development, or Telecom Analytics.
• Strong experience in Python for data processing and automation.
• Hands-on expertise in Apache Airflow for workflow orchestration.
• Good understanding of Telecom OSS/BSS ecosystems.
• Experience in designing and developing ETL/ELT pipelines.
• Knowledge of SQL and database technologies (Oracle, PostgreSQL, MySQL, SQL Server, etc.).
• Experience with data warehousing and big data concepts.
• Understanding of AI/ML data preparation, feature engineering, and model support workflows.
• Strong analytical, debugging, and problem-solving skills.