Job Title: Data Engineer (Python, AI/ML)

Experience Level: 4 to 6 Years

Location: Remote

Job Summary:

We are looking for a highly motivated Data Engineer with expertise in Python, AI/ML, and strong data engineering skills. The ideal candidate will have experience in building and maintaining scalable data pipelines, processing large datasets, and implementing machine learning models. This role involves close collaboration with data scientists and software engineers to design and build solutions that support business insights and analytics.

Key Responsibilities:

- Design, develop, and maintain scalable and reliable ETL pipelines to process large volumes of structured and unstructured data.

- Collaborate with data scientists and AI/ML teams to integrate machine learning models into production.

- Build and maintain data lakes, data warehouses, and distributed computing systems.

- Optimize performance and reliability of data workflows, ensuring data quality and integrity.

- Write efficient Python code to automate data collection, cleaning, and preprocessing tasks.

- Leverage cloud-based services like AWS/GCP/Azure for scalable data infrastructure.

- Work with big data technologies such as Hadoop, Spark, or Kafka to handle large-scale data.





- Implement and maintain data security and privacy standards.

- Collaborate with business and engineering teams to define data needs, design systems, and ensure data pipelines meet analytical requirements.

Required Skills:

- 4 to 6 years of experience as a Data Engineer or similar role.

- Strong expertise in Python programming and related libraries (e.g., Pandas, NumPy, Scikit-learn).

- Solid understanding of AI/ML workflows, algorithms, and model deployment.

- Proficiency with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).

- Experience working with data pipeline tools like Apache Airflow, Luigi, or similar.

- Hands-on experience with cloud platforms such as AWS (S3, EC2, Lambda), Google Cloud Platform, or Microsoft Azure.

- Familiarity with big data technologies like Hadoop, Spark, or Kafka.

- Strong understanding of data modeling, ETL processes, and data governance.

- Ability to optimize and maintain CI/CD pipelines for data workflows.

Positive to Have:

- Experience with containerization technologies like Docker and Kubernetes.

- Familiarity with MLOps and automating the deployment of machine learning models.

- Knowledge of data visualization tools (e.g., Tableau, Power BI, Looker).

📌 Data Engineer (Python /AI/ML) (Chennai)
🏢 RLE
📍 Chennai