Senior Data Architect

Tezo is a new generation Digital & AI solutions provider, with a history of creating remarkable outcomes for our customers. We bring exceptional experiences using cutting-edge analytics, data proficiency, technology, and digital excellence.

Role:
Senior Data Architect

Experience :8-12 years

Location:

Hyderabad

As a Senior Data Architect in our Internal Services Business Pod, you will play a key role in designing and owning the enterprise data architecture that underpins both AI‑enabled capabilities and the core data needs of internal applications and platforms.

Your Day-to-Day May Include:

- Work hand in hand with cross‑functional teams including product managers, AI engineers, platform architects, and business stakeholders to translate complex business and AI requirements into scalable data architectures and implementation plans.
- Design logical and physical data models supporting core application data domains, as well as structured and unstructured data across analytics, enterprise search, and AI/LLM workloads.
- Architect, build, and maintain robust data ingestion and transformation pipelines using Python and SQL, integrating enterprise systems and document repositories into Snowflake and Azure data platforms to support application features
- Prepare and structure data for both operational application use and AI consumption, including document sourcing, enrichment, parsing, metadata modeling, and data quality controls to support embedding, retrieval, feature development, and downstream AI services.
- Design, implement, and optimize data storage, transformation, and access patterns in Snowflake to ensure performance, reliability, and scalability for enterprise workloads.
- Leverage Azure data services like Data Factory, Fabric to orchestrate and operationalize enterprise data flows aligned with AI and analytics use cases.
- Partner with architecture and governance teams to implement data classification, lineage, and logical access controls that enforce security, privacy, and regulatory requirements.
- Participate actively in agile ceremonies, conduct design and code reviews, contribute to CI/CD pipelines, and promote SDLC best practices across data engineering initiatives.

Technical Skills and

Qualifications:

- 8–12 years of experience in data engineering, data architecture, or related roles in enterprise environments.
- Strong hands‑on experience designing and implementing modern data architectures and pipelines supporting analytics, enterprise platforms, and AI workloads.
- Advanced SQL skills and proven experience designing data models that support performance, governance, and downstream AI/analytics use cases.
- Hands‑on experience with Snowflake, including data ingestion, transformations, performance optimization, and secure data access patterns.
- Experience using Python to build and operationalize data pipelines, transformations, and integration services.
- Familiarity with Azure data services such as Data Factory, Fabric / One Lake, and related orchestration and monitoring tools.
- Experience supporting AI or GenAI initiatives by preparing enterprise data for LLMs, RAG, enterprise search, or semantic retrieval use cases.
- Understanding of data security, access control, and compliance considerations in regulated environments.