Data / Solutions Architect

Syren Cloud Inc.; Hyderabad; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Syren Cloud Inc. is seeking an experienced Data / Solutions Architect in Hyderabad, India to design, build, and lead scalable enterprise data and AI solutions. The role requires deep expertise in modern data architectures and strong stakeholder management skills.

The ideal candidate should possess 8-12+ years of experience in data engineering or architecture, along with a Bachelor's or Master's degree in Computer Science. Excellent communication and understanding of cloud platforms are essential.

Qualifications

• 8-12+ years of experience in data engineering, analytics, or solution architecture.
• Proven experience as a Data Architect / Solutions Architect / AI Architect.
• Strong understanding of data governance, security, and compliance.

Responsibilities

• Design and implement end-to-end data architectures including data lakes.
• Build scalable batch and streaming data pipelines using modern data engineering frameworks.
• Lead architecture discussions and technical workshops.

Skills

Modern data architectures

Cloud platforms

AI/ML solutions

Databricks ecosystem

Python

SQL

Spark

Stream processing frameworks

MLflow

Vector Search

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Databricks

Delta Lake

Unity Catalog

Job description

We are looking for an experienced Data / Solutions Architect to design, build, and lead scalable enterprise data and AI solutions. This role involves working closely with business stakeholders, engineering teams, and leadership to deliver robust, secure, and high-performance data platforms across cloud environments.

The ideal candidate will bring deep expertise in modern data architectures, cloud platforms, and AI/ML solutions, along with strong stakeholder engagement skills.

Key Responsibilities

• Design and implement end-to-end data architectures including data lakes, lakehouse, and data warehouses
• Build scalable batch and streaming data pipelines using modern data engineering frameworks
• Architect enterprise-grade solutions using Databricks, Delta Lake, and Unity Catalog
• Define architecture standards, best practices, and governance frameworks
• Lead design and implementation across cloud platforms (AWS, Azure, GCP)
• Build multi-cloud and hybrid data architectures where required
• Optimize data systems for performance, scalability, and cost efficiency
• Enable advanced analytics, AI/ML, and Generative AI use cases
• Implement ML lifecycle management (MLflow) and data science enablement
• Design and deploy RAG-based systems, vector search, and AI-driven analytics solutions
• Collaborate with data scientists and engineers to operationalize models

Stakeholder Management

• Work with business leaders, product owners, and C-level stakeholders to translate business needs into technical solutions
• Lead architecture discussions, technical workshops, and solution roadmaps
• Provide thought leadership and guidance across delivery teams

Delivery & Optimization

• Oversee implementation of data solutions ensuring high-quality delivery
• Conduct performance tuning (e.g., partitioning, clustering, indexing strategies)
• Drive cost optimization initiatives and efficiency improvements
• Mentor and guide engineering teams

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Experience

• 8–12+ years of experience in data engineering, analytics, or solution architecture
• Proven experience as a Data Architect / Solutions Architect / AI Architect

Technical Skills

• Strong experience with Databricks ecosystem & Lakehouse architecture
• Delta Lake, Unity Catalog
• Programming: Python, SQL, Spark
• Experience in stream processing frameworks
• Familiarity with:
  • MLflow, Vector Search
  • BI tools and AI analytics platforms

Preferred Skills

• Experience in Generative AI and RAG architectures
• Databricks or cloud certifications (AWS/Azure/GCP)
• Exposure to multiple industries (Banking, FMCG, Healthcare, etc.)
• Strong understanding of data governance, security, and compliance
• Strong problem-solving and analytical thinking
• Excellent communication and stakeholder management skills
• Ability to work across global teams and environments
• Leadership and mentoring capabilities

Sample Impact Areas (Illustrative)

• Reduce processing time of pipelines from days to hours
• Improve system performance and reduce cloud costs (20–30%)
• Build enterprise-grade Lakehouse platforms for large-scale analytics
• Enable AI-powered insights accelerating decision-making