Snowflake Platform Engineer

In-Person Interview Mandatory

Job Description:

We are seeking a Snowflake Platform Engineer to join our dynamic team. The ideal candidate will have strong experience in AWS data lake services, Snowflake, and Python-based data engineering and a proven ability to design, build, and operate scalable cloud data platforms and migration pipelines.

Responsibilities:

• Design, build, and maintain cloud-native data pipelines and services on AWS and Snowflake.
• Implement data lake architectures using Lake Formation, Glue, Step Functions, and Lambda.
• Develop Python, Shell, and UNIX-based solutions for data ingestion, transformation, and orchestration.
• Create and manage infrastructure as code with Terraform for AWS and Snowflake resources.
• Optimize Snowflake performance and implement features including Snowflake Cortex and Streamlit apps.
• Enable data movement using AWS CLI, Python APIs, Spark, and Boto3 with secure governance.
• Support analytics services including Athena, S3 Select, EMR, and Redshift as needed.
• Implement CI/CD pipelines using Bitbucket/Git and Jenkins with approvals in ServiceNow.
• Monitor and troubleshoot using AWS CloudWatch and Splunk with effective logging and tracing.
• Schedule and orchestrate workloads with Control-M or similar tools.

Required Skills & Qualifications:

• 5–6 years of hands-on software development and data engineering experience.
• Proficiency in Python, Shell scripting, and UNIX.
• Strong experience with Snowflake, including performance tuning and data modeling.
• Snowflake Cortex and Streamlit experience.
• Hands-on with AWS data lake services: Lake Formation, Glue, Step Functions, and Lambda.
• Experience with Terraform for infrastructure as code in AWS and Snowflake ecosystems.
• Data movement expertise using AWS CLI, Python API, Spark, and Python Boto3.
• Familiarity with analytics and compute services: Athena, S3 Select, EMR, Redshift, S3, and EC2.
• Knowledge of scheduling tools, with Control-M preferred.
• CI/CD experience with Bitbucket/Git and Jenkins, and change management via ServiceNow.
• Monitoring and log tracing using AWS CloudWatch and Splunk.

Preferred Skills:

• Knowledge on AI agentic workflows, MCP servers, or AI/ML platforms such as Databricks.
• Prior work in Agile teams delivering cloud data solutions.