Data Architect

Location:

Remote, with occasional onsite presence

Dynanet started with a focus on IT infrastructure and operations, helping organizations enhance their networks and overcome the limitations of 1990s technology. From strengthening communication channels to introducing innovative ways to collaborate and share information, Dynanet played a crucial role in shaping the early stages of digital transformation. The company’s efforts helped organizations build the very fabric of connectivity that now powers our modern world.

Over the last three decades, Dynanet has grown into a trusted partner for organizations looking to innovate boldly and transform seamlessly. While technology continues to evolve and unlock new opportunities, for nearly 30 years, Dynanet remains committed to delivering cutting‑edge solutions that drive lasting change for its customers. Through agility, foresight, and an unwavering dedication to excellence, Dynanet continues to empower organizations to thrive in a rapidly changing digital landscape.

Our story is more than just a story of technology – it’s a story of vision, growth, and transformation that has shaped the past and continues to pave the way for the future.

We are seeking an experienced Data Architect to design, build, and optimize cloud‑based data platforms that support traditional enterprise workloads as well as modern AI and Large Language Model (LLM) applications. This role requires deep, hands‑on expertise across relational, No

SQL, and vector databases
, with a strong focus on scalability, performance, security, and reliability in the cloud. The ideal candidate is equally comfortable designing data models, tuning queries, enabling semantic search and embeddings, and collaborating with data science and AI engineering teams.

• Architect, design, and implement cloud‑native database solutions across relational, No
  
  SQL, and vector database technologies.
• Design and optimize data models, schemas, indexing strategies
  , and storage patterns for performance and scalability.
• Build and manage vector databases to support similarity search, recommendations, and AI inference pipelines.
• Collaborate with AI/ML engineers, application developers, and platform teams to integrate databases into end‑to‑end systems.
• Ensure high availability, disaster recovery, security, and compliance across all database platforms.
• Optimize cost, performance, and reliability in cloud environments
  .
• Implement monitoring, alerting, backup, and automation for database operations.
• Provide technical leadership, documentation, and best‑practice guidance to engineering teams.
• Evaluate and recommend new database technologies and cloud services as requirements evolve.

• 5+ years of hands‑on experience designing and supporting database systems
  .
• 5-8 years of strong expertise in relational databases (e.g.,
  PostgreSQL
  , MySQL, Oracle, SQL Server, Amazon Aurora).
• Strong SQL skills and solid understanding of query optimization and performance tuning.
• Knowledge of data security, encryption, access controls, and compliance requirements.
• Ability to translate business and application requirements into scalable data architectures.

• Experience with Dev Ops or Data Ops practices.
• Experience with LLM platforms (e.g., OpenAI, Azure OpenAI, Amazon Bedrock, Hugging Face).
• Background in designing high‑throughput, low‑latency systems.
• Database Architect certifications (AWS, Azure, or GCP) are a plus.
• Hands‑on experience with No
  
  SQL databases (e.g., MongoDB, DynamoDB, Cassandra, Couchbase).
• Practical experience with vector databases and similarity search (e.g., Pinecone, Milvus, Weaviate, pgvector, Open Search/Elastic vector search).
• Experience supporting A…