Live opening · Posted 5 days ago

Data Engineer

UST · Noida, Uttar Pradesh, India (Hybrid)
Linkedin Hybrid
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyUST
LocationNoida, Uttar Pradesh, India (Hybrid)
Work modeHybrid
SourceLinkedin
Listed5 days ago

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About the role

Description supplied by the original job listing.

We are looking for a highly skilled Data Engineer with strong expertise in SQL, PySpark, Python, and Pandas. The ideal candidate will also have proven team leadership capabilities, enabling them to guide and mentor a team while delivering scalable data solutions. Experience with Generative AI and prompt engineering is a strong plus.
Exp: 4+ years
Job Location: Noida
Mode of interview: F2F interview
Key Responsibilities
Design, develop, and optimize scalable data pipelines and ETL processes.
Work extensively with large datasets using SQL and PySpark.
Write clean, efficient, and maintainable code in Python.
Perform data manipulation and analysis using Pandas.
Lead and mentor a team of data engineers, ensuring best practices and high-quality deliverables.
Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders.
Ensure data quality, integrity, and governance across systems.
Optimize data workflows for performance and scalability.
Participate in architecture discussions and contribute to technical strategy.
Stay updated with emerging technologies, especially in Generative AI.
Required Skills & Qualifications
Strong proficiency in SQL for data querying and transformation.
Hands-on experience with PySpark for big data processing.
Advanced programming skills in Python.
Expertise in Pandas for data analysis and manipulation.
Proven experience in leading or managing a team.
Strong problem-solving and analytical skills.
Experience working with cloud platforms (AWS, Azure, or GCP).
Excellent communication and collaboration skills.
Experience with Generative AI concepts and applications.
Knowledge of Prompt Engineering techniques.
Familiarity with machine learning workflows and tools.
Exposure to data warehousing

Work arrangement
Hybrid

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