Application Developer

Dentsu Global Services; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Dentsu Global Services is seeking an experienced Data Architect/Snowflake specialist to design scalable, secure data platforms. You will lead architecture for data ingestion, storage, governance, and analytics, and drive modern cloud migrations.

The role emphasizes hands-on Snowflake optimization, Python and SQL development, and building Generative AI-enabled solutions, with leadership over engineering teams and collaboration with stakeholders.

Qualifications

• Bachelor's or Master's in CS/IT/Engineering or data science.
• 10+ years in data engineering, warehousing, architecture, or solution architecture.
• 5+ years hands-on Snowflake architecture, implementation, and optimization.

Responsibilities

• Design scalable, secure data solutions using Snowflake and cloud tech.
• Define end-to-end data ingestion, transformation, storage, governance, and analytics.
• Architect and optimize Snowflake environments for critical workloads.
• Lead migration from legacy platforms to Snowflake and cloud-native architectures.
• Provide architectural leadership and conduct design reviews with teams.
• Establish governance, security, performance, and cost optimization practices.

Skills

SQL

Python

Application development

AWS

Snowflake (good to have)

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Snowflake

Snowpark

Snowpipe

Dynamic Tables

Job description

Required Skills : SQL, Python, Application Development, AWS, Snowflake (good to have)

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 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.
• 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.
• Data Governance: Data Security, Data Quality Management, Metadata Management, Compliance, Access Controls.
• Visualization & Analytics: Power BI, Tableau, Advanced Analytics.