Python Data Engineer
Summary
Build and maintain ETL/ELT pipelines, data warehouses, and lakes using Python and SQL on cloud platforms like AWS/Azure.
Responsibility:
- Design, develop, and maintain robust ETL/ELT data pipelines.
- Build and optimize data warehouses, data lakes, and data models.
- Integrate data from multiple internal and external sources.
- Monitor, troubleshoot, and improve data pipeline performance and reliability.
- Ensure data quality, integrity, security, and governance standards are met.
- Collaborate with cross-functional teams to understand business data requirements.
- Automate data workflows and improve operational efficiency.
- Document data architecture, workflows, and engineering best practices.
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent experience).
- Minimum 3 years of experience as Data Engineer versed with building ETL/ELT pipelines.
- Strong proficiency in SQL and Python.
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with data warehouse technologies such as Snowflake, Amazon Redshift, BigQuery, or Azure Synapse.
- Excellent communication and collaboration abilities.