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Data Engineer - (AI and Python)

30+ days ago 2026/09/03
Other Business Support Services
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Job description

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.
Market Competitive Salary Leaves Health Insurance Hybrid Work Model 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.
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