Data Engineer - Python Programming

Description :

Job Summary :

We are seeking a skilled Data Engineer with strong expertise in Python and Apache Airflow to design, build, and maintain scalable data pipelines for enterprise applications.

The ideal candidate will work closely with data scientists, analysts, and product teams to enable high-quality, reliable, and accessible data for analytics and business intelligence purposes.

Key Responsibilities :

- Design, develop, and maintain ETL/ELT pipelines for structured and unstructured data using Python and Apache Airflow

- Build and optimize data workflows for ingestion, transformation, and loading across multiple sources

- Ensure data quality, integrity, and consistency through automated validation and monitoring

- Collaborate with data scientists and analysts to deliver analytics-ready datasets

- Implement scheduling, orchestration, and automation of workflows using Airflow DAGs

- Optimize existing pipelines for performance, scalability, and reliability

- Develop and maintain documentation for data models, pipelines, and workflows

- Monitor and troubleshoot data pipelines and workflows to ensure high availability

- Work with DevOps/Cloud teams to deploy and scale data pipelines on cloud platforms (AWS, GCP, Azure)

- Ensure compliance with data security, privacy, and governance policies

Required Skills & Qualifications :

- Bachelors degree in Computer Science, Information Systems, Engineering, or a related field

- 2+ years of experience in data engineering or related roles

- Strong programming skills in Python and experience with scripting for ETL/ELT

- Hands-on experience with Apache Airflow for workflow orchestration

- Proficiency in SQL for data querying, manipulation, and optimization

- Experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra)

- Knowledge of data modeling, schema design, and data warehousing concepts

- Familiarity with cloud-based data platforms (AWS Redshift, BigQuery, Snowflake)

- Understanding of CI/CD pipelines, version control (Git), and deployment best practices