Technical Architect

Job Description:
Solution Architect (Snowflake, Python & SQL)Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
10+ years of experience in Data Engineering, Data Warehousing, Data Architecture, or Solution Architecture.
Minimum 5+ years of hands-on experience with Snowflake architecture, implementation, and optimization.
Proven experience designing enterprise-scale cloud data platforms and analytics solutions.
Strong experience with data modernization, cloud migration, and digital transformation initiatives.
Experience leading technical teams and collaborating with cross-functional stakeholders.
Excellent communication, presentation, and stakeholder management skills.
Required Skills
Snowflake: Snowflake Architecture, Snowpark, Snowpipe, Streams & Tasks, Dynamic Tables, Data Sharing, Performance Tuning, Cost Optimization.
Programming: Python, SQL, PySpark, Pandas, NumPy.
Data Engineering: ETL/ELT Design, Data Pipelines, Data Warehousing, Data Lakehouse Architecture, Data Modeling.
Generative AI & AI Technologies: Azure OpenAI, OpenAI APIs, LLMs, RAG (Retrieval-Augmented Generation), AI Agents, Prompt Engineering, Vector Databases, LangChain, Semantic Kernel.
Cloud Platforms: Microsoft Azure (preferred), Azure Data Factory, Azure Databricks, Azure AI Services, Microsoft Fabric.
DevOps & Automation: GitHub, Azure DevOps, CI/CD, Docker, Kubernetes, Terraform.
Data Governance: Data Security, Data Quality Management, Metadata Management, Compliance, Access Controls.
Visualization & Analytics: Power BI, Tableau, Advanced Analytics.
Key Responsibilities
Design and implement scalable, secure, and high-performing enterprise data solutions using Snowflake and cloud technologies.
Define end-to-end architecture for data ingestion, transformation, storage, governance, and analytics.
Architect and optimize Snowflake environments to support business-critical workloads.
Develop and review Python- and SQL-based solutions for data engineering and analytics use cases.
Design and implement Generative AI solutions including LLM-powered applications, AI assistants, intelligent search, and enterprise copilots.
Build and govern RAG-based architectures integrating structured and unstructured enterprise data.
Collaborate with business stakeholders to convert business requirements into scalable technical solutions.
Lead migration initiatives from legacy data platforms to Snowflake and cloud-native architectures.
Establish best practices for data governance, security, performance optimization, and cost management.
Provide architectural leadership, conduct design reviews, and mentor engineering teams.
Evaluate emerging AI, cloud, and data technologies and recommend adoption strategies.
Drive automation, innovation, and continuous improvement initiatives across data and AI platforms.
Support solution estimation, technical planning, risk identification, and mitigation strategies.
Create architecture documentation, technical roadmaps, and governance artifacts.
Ensure compliance with enterprise standards, security policies, and regulatory requirements.
Location:
DGS India - Bengaluru - Manyata N1 Block
Brand:
Merkle
Time Type:
Full time
Contract Type:
Permanent