Data Architect Lead

1 month ago

Chennai, Tamil Nadu, India QBrainX Full time

About This Role:

As a Data Engineering Lead at QBrainX, you will be responsible for designing and implementing scalable and efficient data solutions. Your expertise in Snowflake, Azure, and Databricks technologies will be crucial in building and optimizing data warehouses. You will collaborate with cross-functional teams to understand business requirements and provide technical leadership in designing and implementing data pipelines, ETL processes, and data warehousing solutions.

Key Responsibilities:

1. Architect and Design Data Solutions:
- Collaborate with cross-functional teams to understand business requirements and design scalable and efficient data solutions.
- Define data architectures, data models, and data integration strategies to meet business objectives.

2. Snowflake Expertise:
- Leverage your in-depth knowledge of Snowflake technologies to build and optimize data warehouses.
- Develop and maintain Snowflake data models and schemas to support reporting and analytics needs.
- Familiarity with Snowflake best practices, such as cost analysis, resource allocation, data loading strategies (e.g., bulk loading, incremental loading), and security configurations.

3. Azure and Databricks Proficiency:
- Utilize Azure cloud services and Databricks platforms to manage and process large datasets efficiently.
- Build, deploy, and maintain data pipelines on Azure Data Factory, Azure Databricks, and other Azure services.

4. Data Warehousing and Integration:
- 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.

5. SQL and PL/SQL Mastery:
- 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.

6. Performance Tuning and Optimization:
- Continuously monitor and enhance the performance of data pipelines and data storage systems.
- Troubleshoot and resolve data-related issues to minimize downtime.

7. Documentation and Collaboration:
- Document data engineering processes, data flows, and architectural decisions.
- Collaborate with data scientists, analysts, and other stakeholders to ensure data availability and usability.

8. Security and Compliance:
- Implement data security measures and adhere to compliance standards (e.g., GDPR, HIPAA) to protect sensitive data.

Requirements:

- 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.

What We Offer:

- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Collaborative and dynamic work environment.

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