DATA Modeler

Role Description:

The candidate should be highly skilled in various data modeling techniques, including Entity-Relationship Diagrams (ER Diagrams), Visual representation of data entities and their relationshipsand Data Flow Diagrams (DFDs), should be proficient in normalization methods to organize data, reduce redundancy, and enhance data integrity.Should expert in designing, implementing, and managing database solutions on Google Cloud Platform (GCP). The role focuses on building scalable, high-availability, and secure databases, utilizing GCP services like Cloud SQL, Cloud Spanner, and BigQuery. Key responsibilities include data migration, performance optimization, and collaboration with other teams.

Key SkillandKey Responsibilities:

• Designing Data Models: Creating conceptual, logical, and physical data models that represent business processes and workflows.
• Understanding Business Needs: Identifying and analyzing data requirements from various stakeholders and business units.
• Data Quality and Integrity :Implement data quality checks and validations to ensure the accuracy, consistency, and reliability of data across the database.
• GCP Database Expertise: Strong understanding of GCP database services, including Cloud SQL (MySQL, PostgreSQL, SQL Server), Cloud Spanner, and BigQuery.
• SQL Proficiency: Strong skills in SQL, including query optimization, stored procedures, and database administration.
• Performance Tuning and Optimization: Analyze database performance, identify bottlenecks, and implement solutions to improve query speed, scalability, and overall efficiency.
• Data Migration and ETL: Experience with data migration tools and techniques, including ETL processes and data transformation. Migrate databases from on-premises or other cloud environments to GCP, ensuring data integrity and minimal downtime.
• Security and Compliance: Implement and maintain database security measures, including access control, encryption, and compliance with relevant industry standards.
• Monitoring and Troubleshooting: Monitor database health, performance, and availability, proactively identify and resolve issues, and ensure data availability.
• Collaboration and Communication: Work closely with data engineers, architects, and other stakeholders to understand requirements, design solutions, and ensure effective communication.
• Cloud Infrastructure: Familiarity with cloud infrastructure concepts, including virtualization, networking, and storage.
• Problem-solving and Analytical Skills: Ability to identify and resolve database issues, troubleshoot performance problems, and analyze data trends.

Additional Desired Skills:

• Cloud Spanner Expertise: Experience with Google's globally distributed, highly scalable database.
• BigQuery Expertise: Knowledge of BigQuery's capabilities for data warehousing and analytics.
• Data Engineering Tools: Familiarity with data integration tools and pipelines, including Apache Airflow, Dataflow, and Dataproc.
• Automation and Infrastructure as Code: Proficiency with tools like Terraform or CloudFormation for automating infrastructure provisioning.
• Cloud Native Development: Experience with containerization, microservices, and cloud-native application development.