Data Engineering Lead/Architect
3 weeks ago
Job Summary:
We are seeking an experienced Data Engineering Lead/Architect to join our team at QBrainX. As a key member of our data engineering team, you will be responsible for designing and implementing scalable and efficient data solutions, leveraging your expertise in Snowflake, Azure, and Databricks technologies.
Key Responsibilities:- Collaborate with cross-functional teams to understand business requirements and design data solutions.
- Define data architectures, data models, and data integration strategies to meet business objectives.
- Provide technical leadership in designing and implementing data pipelines, ETL processes, and data warehousing solutions.
- Leverage your expertise in Snowflake to build and optimize data warehouses.
- Develop and maintain Snowflake data models and schemas to support reporting and analytics needs.
- Utilize Azure cloud services and Databricks platforms to manage and process large datasets efficiently.
- Implement best practices for data warehousing, ensuring data quality, consistency, and reliability.
- Create and manage data integration processes, including real-time and batch data movement between systems.
- Write complex SQL and PL/SQL queries to extract, transform, and load data effectively.
- Optimize SQL queries and database performance for high volume data processing.
- Continuously monitor and enhance the performance of data pipelines and data storage systems.
- Troubleshoot and resolve data-related issues to minimize downtime.
- Document data engineering processes, data flows, and architectural decisions.
- Collaborate with data scientists, analysts, and other stakeholders to ensure data availability and usability.
- Implement data security measures and adhere to compliance standards to protect sensitive data.
- Bachelor's or master's degree in computer science, Information Technology, or related field.
- Over 10 years of experience in Data Engineering, with a strong focus on architecture.
- Proven expertise in Snowflake, Azure, and Databricks technologies.
- Comprehensive knowledge of data warehousing concepts, ETL processes, and data integration techniques.
- Exceptional SQL and PL/SQL skills.
- Experience with performance tuning and optimization of data pipelines.
- Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Excellent communication skills to convey technical concepts to non-technical stakeholders.
- Certifications in relevant technologies (e.g., Snowflake, Azure) are a plus.
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