Data Engineer - (AI and Python)

FlatGigs is seeking a skilled Data Engineer (AI and Python) to join our dynamic team. In this role, you will build and maintain robust data pipelines and infrastructure that power AI-driven applications and analytics. You will work closely with data scientists and AI engineers to support scalable machine learning workflows and drive data innovation.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Python to handle large volumes of structured and unstructured data.
• Collaborate with AI teams to develop data solutions that enable efficient model training, evaluation, and deployment.
• Implement data ingestion, cleansing, and transformation processes to ensure high-quality datasets for AI workflows.
• Optimize data workflows and storage solutions for performance and reliability.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and monitor data pipelines and related infrastructure.
• Maintain documentation and enforce data governance and compliance policies.
• Participate in code reviews, testing, and continuous integration to deliver robust production-ready data solutions.

Requirements

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 3+ years of professional experience in data engineering with a focus on AI and ML workflows.
• Strong proficiency in Python programming and experience using libraries such as Pandas, NumPy, and Airflow.
• Hands-on experience building and managing ETL/ELT pipelines.
• Good understanding of cloud platforms (AWS, Azure, or GCP) and familiarity with deploying data infrastructure.
• Experience with SQL and NoSQL databases.
• Familiarity with container orchestration tools such as Docker and Kubernetes is a plus.

Preferred Skills

• Knowledge of AI/ML concepts and ability to collaborate effectively with data science teams.
• Experience with distributed data processing frameworks like Apache Spark.
• Understanding of data security, compliance, and best practices in data engineering.

Benefits

Market Competitive Salary

Leaves

Health Insurance

Hybrid Work Model