Dhira | Principal Data Architect | india
4 weeks ago
Position Overview:
We are seeking a Principal Data Architect with 15+ years of experience who has a comprehensive understanding of the evolution of databases , from OLTP to OLAP, and relational systems to NoSQL, Graph, and emerging Vector Databases . This role requires deep expertise in data modeling , from traditional ER modeling to advanced dimensional, graph, and vector schemas, along with a strong grasp of the history, best practices, and future trends in data management.
The ideal candidate will bring both historical context and cutting-edge expertise to architect scalable, high-performance data solutions, driving innovation while maintaining strong governance and best practices. This is a leadership role that demands a balance of technical excellence, strategic vision, and team mentorship.
Responsibilities
1. Data Modeling Expertise:
- Design and implement Entity-Relationship Models (ER Models) for OLTP systems, ensuring normalization and consistency.
- Transition ER models into OLAP environments with robust dimensional modeling, including star and snowflake schemas.
- Develop hybrid data models that integrate relational, NoSQL, Graph, and Vector Database schemas.
- Establish standards for schema design across diverse database systems, focusing on scalability and query performance.
2. Database Architecture Evolution:
Architect solutions across the database spectrum-
- Relational databases (PostgreSQL, Oracle, MySQL)
- NoSQL databases (MongoDB, Cassandra, DynamoDB)
- Graph databases (Neo4j, Amazon Neptune
- Vector databases (Pinecone, Weaviate, Milvus).
- Implement hybrid data architectures combining OLTP, OLAP, NoSQL, Graph, and Vector systems for diverse business needs.
- Ensure compatibility and performance optimization across these systems for real-time and batch processing.
3 Data Warehousing and Analytics:
- Lead the development of enterprise-scale Data Warehouses capable of supporting advanced analytics and business intelligence.
- Design high-performance ETL/ELT pipelines to handle structured and unstructured data with minimal latency.
- Optimize OLAP systems for petabyte-scale data storage and low-latency querying.
4. Emerging Database Technologies:
- Drive adoption of Vector Databases for AI/ML applications, enabling semantic search and embedding-based queries.
- Explore cutting-edge technologies in data lakes, lakehouses, and real-time processing systems.
- Evaluate and integrate modern database paradigms, ensuring scalability for future business requirements.
5. Strategic Leadership:
- Define the organization’s data strategy , aligning with long-term goals and emerging trends.
- Collaborate with business and technical stakeholders to design systems that balance transactional and analytical workloads.
- Lead efforts in data governance, ensuring compliance with security and privacy regulations.
6. Mentorship and Innovation:
- Mentor junior architects and engineers, fostering a culture of learning and technical excellence.
- Promote innovation by introducing best practices, emerging tools, and modern methodologies in data architecture.
- Act as a thought leader in database evolution, presenting insights to internal teams and external forums.
Required Skills & Qualifications:
• Experience:
- 15+ years of experience in data architecture, with demonstrated expertise across OLTP, OLAP, NoSQL, Graph, and Vector databases.
- Proven experience designing and implementing data models across relational, NoSQL, graph, and vector systems.
- A strong understanding of the evolution of databases and their impact on modern data architectures.
• Technical Proficiency:
- Deep expertise in ER modeling , dimensional modeling, and schema design for modern database systems
- Proficient in SQL and query optimization for relational and analytical databases.
- Hands-on experience with NoSQL databases like MongoDB, Cassandra, or DynamoDB.
- Strong knowledge of Graph databases (Neo4j, Amazon Neptune) and Vector databases (Pinecone, Milvus, or Weaviate).
- Familiarity with modern cloud-based DW platforms (e.g., Snowflake, BigQuery, Redshift) and lakehouse solutions.
• Knowledge of Data Practices:
- Historical and practical understanding of data practices, from schema-on-write to schema-on-read approaches.
- Experience in implementing real-time and batch processing systems for diverse workloads.
- Strong grasp of data lifecycle management, governance, and security practices.
• Leadership and Communication:
- Ability to lead large-scale data initiatives, balancing technical depth and strategic alignment.
- Excellent communication skills to articulate complex ideas to technical and non-technical audiences.
- Proven ability to mentor and upskill teams, fostering a collaborative environment
Preferred Skills:
• Experience integrating Vector Databases into existing architectures for AI/ML workloads.
• Knowledge of real-time streaming systems (Kafka, Pulsar) and their integration with modern databases.
• Certifications in data-related technologies (e.g., AWS, GCP, Snowflake, Neo4j).
• Hands-on experience with BI tools (e.g., Tableau, Power BI) and AI/ML platforms.
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