Data Architect / AI Enterprise Architect

We are currently hiring for a Data Architect / AI Enterprise Architect opportunity based in Hyderabad . Based on your profile, I believe your experience may be relevant to this requirement.

The role requires a strong combination of Enterprise Data Architecture, hands-on Data Engineering, Cloud Data Platforms, AI/Intelligent Data Solutions, and technical leadership .

Position: Data Architect / AI Enterprise Architect

Experience: 15+ Years

Location: Hyderabad

Work Model: Hybrid – 3 Days/Week from Client Office

Employment Type: Full-Time

Required experience and capabilities

· Bachelor’s degree in computer science, Engineering, Information Systems or a related discipline, or equivalent practical experience.

·   15+ years of overall experience

in Data engineering and enterprise platforms.

·   3+ years of experience in

Analytics, AI and intelligent data solutions.

· Significant experience designing enterprise data platforms and delivering data engineering solutions in complex, multi-team environments.

· Demonstrated hands-on development experience with Python and advanced SQL, including performance optimization and production support.

· Practical experience with data integration, data modeling, Data Warehouse, Data Lake and Lakehouse architecture.

· Experience with at least one major cloud platform and modern cloud data services; ability to apply architecture principles across Azure, AWS or GCP.

· Working knowledge of data governance, quality, metadata, lineage, security and compliance controls.

· Experience with CI/CD, automated testing, monitoring, source control and modern engineering delivery practices.

· Strong analytical, problem-solving and communication skills, with the ability to influence technical decisions and work effectively across functions.

Preferred experience

· Hands-on experience with SnapLogic or Informatica, and platforms such as Snowflake, BigQuery, Redshift, PostgreSQL, SQL Server, Oracle or MongoDB.

· Experience with Collibra, SODA, Power BI, Tableau, infrastructure automation, DataOps or DevSecOps.

· Exposure to AI/ML data platforms, RAG, vector databases, semantic search, MLOps or enterprise copilots.

· Relevant cloud, data architecture, database or data engineering certifications.