Senior Cloud Data Architect

This is a unique opportunity to join our esteemed data engineering team as a seasoned and proficient Senior Python Data Engineer. We are seeking an individual with substantial experience in cloud technologies to play a pivotal role in designing, implementing, and optimizing data pipelines.

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2. Design, develop, and maintain scalable and efficient data pipelines using Python and cloud-based technologies.
3. Implement Extract, Transform, Load (ETL) processes to seamlessly move data from diverse sources into our cloud-based data warehouse.
4. Utilize cloud platforms (e.g., Google Cloud, AWS, Azure) to deploy, manage, and optimize data engineering solutions.
5. Leverage cloud-native services for storage, processing, and analysis of large datasets.
6. Collaborate with data scientists, analysts, and other stakeholders to design effective data models that align with business requirements.
7. Ensure the scalability, reliability, and performance of the overall data infrastructure on cloud platforms.
8. Continuously optimize data processes for improved performance, scalability, and cost-effectiveness in a cloud environment.
9. Monitor and troubleshoot issues, ensuring timely resolution and minimal impact on data availability.
10. Implement data quality checks and validation processes to ensure the accuracy and completeness of data in the cloud-based data warehouse.
11. Collaborate with cross-functional teams to identify and address data quality issues.
12. Work closely with data scientists, analysts, and other teams to understand data requirements and provide technical support.

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• Programming Languages: Proficiency in Python for data engineering tasks, scripting, and automation.
• Data Engineering Technologies: Extensive experience with data engineering frameworks like distributed data processing.
• Understanding and hands-on experience with workflow management tools like Apache Airflow.
• Cloud Platforms: In-depth knowledge and hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
• Familiarity with cloud-native services for data processing, storage, and analytics.
• ETL Processes: Proven expertise in designing and implementing Extract, Transform, Load (ETL) processes.
• SQL and Databases: Proficient in SQL with experience in working with relational databases (e.g., PostgreSQL, MySQL) and cloud-based database services.
• Data Modeling: Strong understanding of data modeling principles and experience in designing effective data models.
• Version Control: Familiarity with version control systems, such as Git, for tracking changes in code and configurations.
• Collaboration Tools: Experience using collaboration and project management tools for effective communication and project tracking.
• Containerization and Orchestration: Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
• Monitoring and Troubleshooting: Ability to implement monitoring solutions and troubleshoot issues in data pipelines.
• Data Quality Assurance: Experience in implementing data quality checks and validation processes.
• Agile Methodologies: Familiarity with agile development methodologies and practices.

We are a dynamic organization focused on delivering innovative data-driven solutions to drive business value. Our team is passionate about leveraging cloud technologies to engineer scalable and efficient data pipelines.