Data Modeler

Job Description:

• Design and Implement Data Models: Develop conceptual, logical, and physical data models tailored for GCP, utilizing tools such as BigQuery, Cloud SQL, and Dataflow.
• Collaborate with Cross-Functional Teams: Work closely with data engineers, data scientists, and business analysts to gather requirements and translate them into effective data modeling solutions on GCP.
• Optimize Data Architecture: Implement best practices for data modeling that enhance performance and scalability of data solutions in GCP environments.
• Data Integration: Integrate diverse data sources into GCP, ensuring seamless data flow into data lakes and warehouses while maintaining data quality.
• Automate Data Processes: Utilize GCP services to automate data ingestion, transformation, and modeling processes, ensuring efficient workflows.
• Monitor and Improve Performance: Continuously assess the performance of data models and implement improvements to meet evolving business needs.
• Stakeholder Engagement: Communicate effectively with stakeholders to understand their data requirements and provide actionable insights based on the developed models.

• Experience: 4+ years of experience in data modeling and architecture, with a strong emphasis on cloud platforms, particularly Google Cloud Platform (GCP).
• Skills: Extensive knowledge of data modeling techniques, cloud data warehousing concepts, and GCP services such as Big Query, Cloud SQL, and Dataflow. Proficient in SQL and familiar with NoSQL databases. Strong analytical skills in data analysis and data preprocessing.
• Qualifications: Bachelor’s or master’s degree in computer science, Data Science, Information Technology, or a related field.
• Competencies: Proven ability to design and implement scalable data models and architecture on GCP. Experience in creating efficient ETL processes and integrating diverse data sources into cloud environments.
• Certifications: Google Cloud Professional Data Engineer certification preferred.
• Knowledge: In-depth understanding of data governance, metadata management, and best practices in cloud-based data architecture.
• Soft Skills: Excellent communication and problem-solving skills, with the capability to convey complex technical concepts to both technical and non-technical stakeholders. Strong collaboration skills to work effectively within cross-functional teams.
• Tools: Experience with data modeling tools (e.g., Erwin, Microsoft Visio), version control systems (Git), CI/CD pipelines, and cloud-based data storage solutions (e.g., BigQuery, Cloud Storage).