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7-12 Years
Not Disclosed

This job is no longer accepting applications

Job Description

We are hiring an experienced Senior Data Engineer with a strong foundation in Python, big data platforms, and an understanding of AI/ML workflows within data engineering. The ideal candidate will work on building scalable and efficient data pipelines, supporting advanced analytics and machine learning initiatives.

Primary Skills Required:

  • Python Programming – Strong hands-on experience in data engineering applications
  • AI/ML Understanding – Familiarity with machine learning concepts, model lifecycle, and how AI integrates into data engineering pipelines
  • BigQuery or Snowflake – Expertise in modern cloud data warehouses for building and optimizing queries and data models
  • Data Engineering – Proven experience in building, maintaining, and optimizing large-scale ETL/ELT data pipelines
  • Ability to collaborate closely with data scientists and ML engineers to enable efficient data access for model training and inference

Responsibilities:

  • Design and implement scalable data pipelines to support analytics and AI/ML use cases
  • Work with cloud-based databases like BigQuery or Snowflake to process and analyze large datasets
  • Collaborate with cross-functional teams including data scientists and business analysts
  • Build data models that feed into AI/ML pipelines
  • Ensure data quality, integrity, and governance across platforms
  • Optimize performance and cost efficiency of data systems

More Info

Key Skills

data pipelines

cloud-based databases

AI/ML pipelines

About Company

Peoplefy is an award-winning talent solutions firm, founded by a group of former software engineers and graduates from India's premier technology institutes, the IITs. Peoplefy leverages advanced technology and a cutting-edge cloud-based software ATS for driving Recruitment Process. Peoplefy excels in early detection of offer backouts with introduction of “Early Warning Mechanism” through AI & other Technologies, making it a standout in the industry.

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