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Data Engineer

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Onsite

Data Engineer

Iris Software

Data Engineer

Skills

SQL QueriesData EngineeringPythonGitData AnalysisAWSPySparkApache Airflow

2 months ago

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Important information


Contract type:

Permanent

Location:

Gurugram, Haryana, India

Work mode:

Onsite

Published on:

27 August 2026

What they need


About Iris

At Iris Software, our vision is to be our clients most trusted technology partner, and the first choice for the industry’s top professionals to realize their full potential.

With over 4,300 associates across India, U.S.A, and Canada, we help our enterprise clients thrive with technology-enabled transformation across financial services, healthcare, transportation & logistics, and professional services.

Our work covers complex, mission-critical applications with the latest technologies, such as high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation.

Working at Iris: Be valued, be inspired, be your best.

At Iris Software, we invest in and create a culture where colleagues feel valued, can explore their potential, and have opportunities to grow.

Our employee value proposition is about “Being Your Best” – as a professional and person. It is about being challenged by work that inspires us, being empowered to excel and grow in your career, and being part of a culture where talent is valued. We’re a place where everyone can belong.

Pls find below JD :

Required Skills & Experience

  • 7–9 years of professional experience as a Data Engineer or in a similar role.

  • Strong expertise in Python, including:

  • Object-Oriented Programming (OOP)

  • Functional programming paradigms

  • Hands-on experience building distributed data pipelines using PySpark.

  • Strong proficiency in SQL (analytical queries, performance tuning, data modeling concepts).

  • Solid experience with AWS cloud services for data engineering workloads.

  • Proven experience with Apache Airflow for workflow orchestration.

  • Experience working with large-scale data processing, structured/unstructured data, and data lakes.

  • Understanding of CI/CD, version control (Git), and DevOps practices for data engineering.

  • Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment

Regards

Neha Fulara

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