Principal Data Architect

4 weeks ago

India Dhira Full time

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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