Data Engineer - (Python, AWS/Azure, Snowflake)

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