Python data modeller

Responsibilities

• Data Modeling: Design, develop, and maintain data models that support business requirements and analytics.
• Data Integration: Collaborate with data engineers to integrate data from various sources into the data warehouse.
• ETL Processes: Develop and optimize ETL (Extract, Transform, Load) processes using Python and relevant frameworks.
• Database Management: Work with SQL and NoSQL databases to ensure efficient data storage and retrieval.
• Collaboration: Work closely with cross-functional teams to understand data requirements and provide solutions.
• Documentation: Create and maintain documentation for data models, ETL processes, and data flows.
• Performance Tuning: Monitor and optimize data models and queries for performance improvements.
• Data Quality: Implement data quality checks and validation processes to ensure data integrity.

Requirements

• Programming Languages: Proficiency in Python, with a strong understanding of data manipulation libraries (eg, Pandas, NumPy).
• Database Technologies: Experience with SQL databases (eg, PostgreSQL, MySQL) and NoSQL databases (eg, MongoDB, Cassandra).
• Data Modeling Tools: Familiarity with data modeling tools (eg, Erwin, Talend) and methodologies (eg, Kimball, Inmon).
• ETL Tools: Experience with ETL tools and frameworks (eg, Apache Airflow, Luigi).
• Data Warehousing: Knowledge of data warehousing concepts and architectures.
• Analytical Skills: Strong analytical and problem-solving skills to derive insights from complex datasets.
• Version Control: Experience with version control systems (eg, Git).

• bachelors degree in Computer Science, Information Technology, or a related field.
• 7 to 10 years of experience in data modeling, ETL development, and data analysis.
• Strong communication skills to effectively convey technical concepts to non-technical stakeholders.
• Experience in Agile methodologies is a plus.