Senior Data Engineer

We are seeking a seasoned and proficient Senior Data Engineer with substantial experience in cloud technologies. As a pivotal member of our data engineering team, you will play a crucial role in designing, implementing, and optimizing data pipelines, ensuring seamless integration with cloud platforms. The ideal candidate will possess a strong command of Python, data engineering principles, and a proven track record of successful implementation of scalable solutions in cloud environments. Responsibilities: 1.Data Pipeline Development: Design, develop, and maintain scalable and efficient data pipelines using Python and cloud-based technologies. Implement Extract, Transform, Load (ETL) processes to seamlessly move data from diverse sources into our cloud-based data warehouse. 2.Cloud Integration: Utilize cloud platforms (e.g., Google Cloud, AWS, Azure) to deploy, manage, and optimize data engineering solutions. Leverage cloud-native services for storage, processing, and analysis of large datasets. 3.Data Modelling and Architecture: Collaborate with data scientists, analysts, and other stakeholders to design effective data models that align with business requirements. Ensure the scalability, reliability, and performance of the overall data infrastructure on cloud platforms. 4.Optimization and Performance: Continuously optimize data processes for improved performance, scalability, and cost-effectiveness in a cloud environment. Monitor and troubleshoot issues, ensuring timely resolution and minimal impact on data availability. 5.Quality Assurance: Implement data quality checks and validation processes to ensure the accuracy and completeness of data in the cloud-based data warehouse. Collaborate with cross-functional teams to identify and address data quality issues. 6.Collaboration and Communication: Work closely with data scientists, analysts, and other teams to understand data requirements and provide technical support. Collaborate with other engineering teams to seamlessly integrate data engineering solutions into larger cloud-based systems. 7.Documentation: Create and maintain comprehensive documentation for data engineering processes, cloud architecture, and pipelines.

The ideal candidate will possess a strong command of Python, data engineering principles, and a proven track record of successful implementation of scalable solutions in cloud environments. Extensive experience with data engineering frameworks like distributed data processing. Understanding and hands-on experience with workflow management tools like Apache Airflow. 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. Proficient in SQL with experience in working with relational databases (e.g., PostgreSQL, MySQL) and cloud-based database services. Strong understanding of data modeling principles and experience in designing effective data models. Familiarity with version control systems, such as Git, for tracking changes in code and configurations. Ability to implement monitoring solutions and troubleshoot issues in data pipelines. Experience in implementing data quality checks and validation processes. Familiarity with agile development methodologies and practices.