AI Data Engineer: Scalable ML Pipelines & Data Quality

EdgeQ Technologies Private Limited

New York (NY)

On-site

USD 90,000 - 130,000

Full time

2 days ago
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Job summary

EdgeQ Technologies Private Limited is seeking a skilled AI Data Engineer to design, build, and maintain scalable data pipelines for AI/ML applications in the United States. The role focuses on developing efficient data workflows using Python, SQL, and Apache Spark and ensuring data quality for ML models.

The ideal candidate brings 2–5 years of data engineering experience, hands-on ETL/ELT pipeline expertise, and a strong foundation in data processing.

Qualifications

  • 2–5 years of professional data engineering experience.
  • Strong programming skills in Python.
  • Advanced knowledge of SQL.
  • Hands‑on experience with Apache Spark.
  • Experience building ETL/ELT pipelines.
  • Experience with cloud platforms and data warehouses is a plus.

Responsibilities

  • Design, build, and maintain scalable data pipelines for AI/ML applications.
  • Build and optimize data processing workflows using Python, SQL, and Apache Spark.
  • Prepare, clean, transform, and validate large datasets for machine learning models.
  • Develop reliable ETL/ELT pipelines and integrate data from multiple sources.
  • Collaborate with data scientists and ML engineers to support model development and deployment.
  • Implement data quality, validation, and monitoring processes.
  • Participate in architecture, code reviews, and technical design discussions.
  • Follow data engineering, security, and software development best practices.

Skills

Python
SQL
Apache Spark
ETL/ELT pipelines

Job description

EdgeQ Technologies Private Limited is seeking a skilled AI Data Engineer to design, build, and maintain scalable data pipelines for AI/ML applications in the United States. The role focuses on developing efficient data workflows using Python, SQL, and Apache Spark and ensuring data quality for ML models.

The ideal candidate brings 2–5 years of data engineering experience, hands-on ETL/ELT pipeline expertise, and a strong foundation in data processing.

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