AI Data Engineer (US)

EdgeQ Technologies Private Limited; New York (NY); Presencial; USD 90.000 - 130.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

SQL

Apache Spark

ETL/ELT pipelines

Descripción del empleo

We are seeking a skilled AI Data Engineer to join our team. You will design, build, and maintain scalable data pipelines that support AI and Machine Learning applications.

Key responsibilities

• Design, develop, 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.

Required 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.

Nice to have

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Knowledge of data warehouses like Snowflake, BigQuery, or Redshift.

• Familiarity with MLOps and machine learning data pipelines.

• Experience with streaming technologies such as Kafka.