Naukri Job Posting Data Engineering Lead (Snowflake with AWS S3)
Job Title: Data Engineering Lead Snowflake with AWS S3
Experience: 10 – 15 Years
Location: Bangalore, Hyderabad, Pune, Chennai, Mumbai,
Notice Period: Immediate to 15 Days
Employment Type: Full-Time
Job Description
We are looking for an experienced Data Engineering Lead with strong expertise in Snowflake, AWS S3, and AWS Cloud to design, develop, and lead enterprise-scale data engineering solutions. The ideal candidate should have extensive experience in data warehousing, ETL pipelines, cloud data platforms, and leading distributed teams.
The role involves building scalable data platforms, enabling analytics and AI use cases, and driving cloud-based data transformation initiatives.
Key Responsibilities
- Design and optimize cloud-based data models, ETL pipelines, and data integration solutions.
- Lead implementation of enterprise Data Warehouse solutions using Snowflake.
- Develop and maintain scalable Data Lake solutions using AWS S3 and AWS services.
- Build and optimize data ingestion, transformation, and orchestration frameworks.
- Lead offshore Data Engineering teams and collaborate with onshore architects and stakeholders.
- Ensure data quality, governance, security, and compliance across cloud platforms.
- Integrate SAP and other enterprise data sources into cloud environments.
- Support AI/ML initiatives through analytics-ready datasets and Lakehouse architectures.
- Optimize SQL queries and improve data platform performance.
- Follow best practices for source code management using GitHub.
Mandatory Skills
Snowflake, AWS S3, AWS Cloud, Data Engineering, Data Warehousing, ETL, SQL, AWS Glue, AWS Lambda, Amazon Redshift, Data Lake, GitHub, Data Governance, Database Management, Data Analysis
Good to Have
- AWS SageMaker
- Lakehouse Architecture
- SAP Data Integration
- SAP ERP Data Models
- AI/ML Data Engineering
Required Qualifications
- 10–15 years of experience in Data Engineering.
- Strong expertise in Snowflake and AWS Cloud ecosystem.
- Hands-on experience with AWS S3, Glue, Lambda, and Redshift.
- Experience designing enterprise data warehouses and data lakes.
- Robust SQL development and performance tuning skills.
- Experience building ETL pipelines and orchestration frameworks.
- Knowledge of data governance, security, and compliance.
- Experience leading technical teams and mentoring engineers.
- Excellent communication and stakeholder management skills.
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