Python Data Architect

Architect and maintain ETL pipelines using Informatica, ensuring data quality and integrity.

Work with large datasets, ensuring efficient data ingestion, transformation, and storage.

Develop and optimize data transformation workflows using PySpark.

Collaborate with cross-functional teams to define technical requirements and deliver solutions.

Troubleshoot and resolve issues in production environments.

Mentor junior developers and contribute to best practices.

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).

5+ years of professional experience as a Python developer.

3+ years of experience with PostgreSQL, including database design and performance tuning.

3+ years of experience developing APIs with Flask or FastAPI.

Proven experience working with large datasets and data-intensive applications.

Experience integrating AI or machine learning models into data pipelines or applications.

Familiarity with Python-based machine learning libraries such as scikit-learn, TensorFlow, or

PyTorch.

2+ years of experience with data transformation using PySpark, Dask, Polars, etc.

Strong understanding of data modeling, data warehousing, and data integration concepts.

Experience with version control systems (e.g., Git).

Excellent problem-solving skills and attention to detail.

Strong communication and teamwork abilities.

Preferred Qualifications:

Hands-on experience with Informatica and ETL processes.

Experience with cloud platforms.

Familiarity with containerization (Docker, Kubernetes).

Knowledge of data visualization tools and techniques.

qualifications:

Design, build, and maintain scalable Python applications for data processing and analytics.

Develop RESTful APIs using Flask or FastAPI.

Implement and optimize complex SQL queries and database structures in PostgreSQL.