Overview
Skills
Job Details
Role: Sr. BigData Architect
Location: Phoenix, AZ (Onsite)
Duration: 12+ Months
Job Description:
We are seeking an experienced Senior Data Architect to modernize and optimize our existing data architecture, primarily focused on virtual assistant conversational data. This includes large data volumes, multi-table structures, and multi-modality data formats, currently hosted in a traditional RDBMS environment. The role involves rethinking the data schemas, fine-tuning performance, and migrating the data to modern technologies like BigQuery or other scalable, efficient platform
Technical Expertise:
Strong experience in designing and managing relational databases (e.g., MySQL, PostgreSQL, Oracle).
Hands-on experience with cloud-based data platforms like Google BigQuery, Snowflake, AWS Redshift, or similar.
Proficiency in Apache Flink, Kafka, SQL and data modeling tools.
Performance Optimization:
Proven track record of fine-tuning large-scale databases, including indexing, partitioning, and query optimization.
Experience in schema redesign and migration strategies.
Modern Data Solutions:
Knowledge of multi-modality data handling and NoSQL solutions (e.g., MongoDB, DynamoDB).
Familiarity with ETL/ELT pipelines and tools like Apache Airflow, DBT, or similar.
Key Responsibilities
Data Architecture Modernization:
Analyze the current RDBMS-based architecture for virtual assistant conversational data.
Redesign and modernize data schemas to support scalability, performance, and multi-modality use cases.
Incorporate emerging data storage technologies such as BigQuery, Snowflake, or other cloud-native platforms.
Optimization and Fine-Tuning:
- Evaluate and improve indexing, partitioning, and sharding strategies to optimize query performance.
- Refactor existing schemas and table structures for efficient data retrieval and storage.
- Implement best practices for data normalization and denormalization as required by the use cases.
Migration Strategy:
- Develop a detailed migration plan for transitioning data from the current RDBMS to modern platforms.
- Ensure data consistency, integrity, and minimal downtime during migration.
- Work with DevOps and engineering teams to automate migration processes and set up monitoring tools.
Support Multi-Modality Data Needs:
- Design data models that can handle multi-modality data (text, images, audio, etc.) effectively.
- Enable seamless integration of new data types into the existing architecture.
Collaboration and Governance:
- Collaborate with engineering, analytics, and AI/ML teams to align the data architecture with their needs.
- Define and enforce data governance, quality standards, and security policies.
- Document architectural decisions and maintain up-to-date diagrams and schemas. 6. Performance Monitoring and Maintenance:
- Implement tools to monitor database performance and identify bottlenecks.
- Proactively recommend improvements to maintain high availability and reliability.
- Plan for future data growth and evolving business requirements.
- Design and implement scalable and reliable data solutions.
- Develop data architecture blueprints and roadmaps.
- Lead the development of data warehousing and ETL processes.
- Ensure data quality and integrity across all systems.
- Collaborate with cross-functional teams to understand data needs and requirements.
- Provide technical guidance and mentorship to junior team members.
- Evaluate and recommend new data technologies and tools.
Collaboration Skills: Excellent communication and collaboration skills to work across teams, including engineers, analysts, and product managers. Ability to translate business needs into scalable, technical data solutions.
Soft Skills: Strategic thinker with a hands-on approach to problem-solving. Strong documentation and organizational skills to manage