Data Architect (Snowflake+Python+AWS)
Coforge · Noida, Uttar Pradesh, India - Hyderabad, Telangana, India - Pune, Maharashtra, India
Coforge · Noida, Uttar Pradesh, India - Hyderabad, Telangana, India - Pune, Maharashtra, India
Share your resume over **Aarushi.Shukla@Coforge.Com** **Job Summary** We are seeking an experienced **Data Architect** to design, develop, and govern scalable cloud-based data platforms. The ideal candidate will possess strong expertise in AWS, Snowflake, and Python, with a proven track record of architecting enterprise data solutions, data warehouses, data lakes, and modern analytics platforms. The candidate will work closely with business stakeholders, data engineers, architects, and leadership teams to build secure, scalable, and high-performance data ecosystems. **Key Responsibilities** - Design and implement enterprise-scale data architecture using AWS Cloud and Snowflake. - Develop and maintain data models, data pipelines, and data integration frameworks. - Architect and optimize modern data warehouse and data lake solutions. - Define data governance, security, metadata management, and data quality standards. - Build scalable ETL/ELT frameworks using Python and cloud-native technologies. - Lead data migration initiatives from legacy platforms to Snowflake. - Collaborate with business and technical stakeholders to translate business requirements into technical solutions. - Design batch and real-time data ingestion frameworks. **Mandatory Skills** **Snowflake** - Strong expertise in Snowflake architecture and implementation. - Experience in Snowflake Data Warehousing, Data Sharing, and Data Lakes. - Knowledge of Virtual Warehouses, Snowpipe, Streams, Tasks, and Time Travel. - Snowflake performance tuning and cost optimization. **AWS** - Hands-on experience with AWS services such as: - S3 - Glue - Lambda - Redshift - EMR - Athena - Step Functions - CloudWatch - IAM - Experience designing cloud-native and serverless data architectures. **Python** - Strong coding experience in Python for data engineering and automation. - Expertise in developing ETL/ELT pipelines and data transformation frameworks. - Experience with Python libraries such as Pandas, PySpark, NumPy, and Boto3.