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Senior Data Engineer

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Onsite

Senior Data Engineer

IRIS SOFTWARE TECHNOLOGIES PRIVATE LIMITED

Senior Data Engineer

Skills

SQL QueriesPythonKafkaMachine LearningAIAWSApache AirflowCompliance

2 months ago

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Important information


Contract type:

Permanent

Location:

Noida, Uttar Pradesh, India

Work mode:

Onsite

Published on:

31 August 2026

What they need


Job Title

Senior Data Engineer

Job Summary

Position Summary: We are seeking an experienced AI Data Engineer to build and optimize data pipelines that power AI/ML solutions across ETS. This role contributes to data collection efforts through the design and deployment of data instruments, oversees aggregation and cleaning processes, and collaborates with data scientists and ML engineers to interpret and implement findings. The position is critical to preparing high-quality, scalable, and compliant data for advanced analytics, automation, and machine learning use cases while supporting data visualization and trend analysis efforts.

Location

Location: Noida, UP, India

Primary Responsibilities

  • Design and implement robust, scalable data pipelines to support AI/ML model development and deployment
  • Clean, transform, and curate structured and unstructured data from diverse sources to ensure model-ready quality
  • Collaborate with data scientists, ML engineers, and business teams to ensure data readiness, usability, and alignment with AI objectives
  • Develop and maintain metadata management, data lineage, and data quality frameworks to support AI governance and compliance
  • Enable advanced feature engineering capabilities and implement real-time data streaming solutions for AI applications
  • Design and deploy data collection instruments and oversee data aggregation processes
  • Ensure data compliance, privacy, and ethical use standards across all AI workflows
  • Support enterprise-wide data initiatives including business glossary development, taxonomy creation, and the DARE program's automation goals

Must Have

  • Python
  • SQL
  • Spark / distributed processing
  • AWS
  • Airflow / orchestration tools
  • Data pipeline automation
  • Data governance

Nice to have

  • Kafka/Kinesis streaming
  • Feature stores
  • LLMready data pipelines
  • MLOps exposure

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