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Technical Architect
Dentsu
Bengaluru, IND
Full-time
Senior · 10+ years experience
Onsite
Discovered 3 weeks ago
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Key Skills for This Role
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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.
- 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.
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:
- Brand:
- Time Type:
- Contract Type
Location:
- Brand:
- Time Type:
- Contract Type:
About Dentsu
Marketing & Advertising69000 employeesFounded 1901
Global integrated growth and transformation partner for organizations.
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