Snowflake Platform Engineer — Data & Automation

Capgemini; Atlanta (GA); Hybrid; USD 103,000 - 129,000; Full time

Benefits offered by this job

Healthcare

401(k)

Paid time off

Parental leave

Flexible work

Job summary

Capgemini is seeking a Snowflake Platform Administrator and Data Engineer to join our Fort Mill, SC team on a hybrid model. You will manage Snowflake environments, build scalable ELT pipelines, and implement security controls across cloud and on‑prem sources.

You will design, monitor, and optimize data workloads, develop CI/CD pipelines, and collaborate with analytics and engineering teams to drive cost efficiency and governance.

Qualifications

• 8+ years IT experience with at least 4+ years hands-on Snowflake experience.
• Strong expertise in Snowflake administration and platform management.
• Hands-on experience with AWS Glue and cloud-based data engineering solutions.
• Advanced proficiency in SQL and Python.

Responsibilities

• Snowflake Platform Administration for development, testing, and production.
• Manage account setup, RBAC, and security controls including SSO/MFA.
• Configure resource monitors and workload management for cost optimization.
• Design cross-region replication and disaster recovery.
• Develop ETL/ELT pipelines using AWS Glue and Snowflake.
• Build data models and data warehouse solutions for analytics.
• Develop CI/CD pipelines for Snowflake deployments and automation with Python.
• Support IaC initiatives using Terraform; monitor and tune pipelines.

Skills

Snowflake Administration

Snowflake Data Engineering

AWS Glue

Python

SQL

AWS Lambda

Apache Airflow

Terraform

CI/CD Pipelines

Snowpark

Data Governance & Security

Tools

Snowflake

AWS

Terraform

Job description

Capgemini is seeking a Snowflake Platform Administrator and Data Engineer to join our Fort Mill, SC team on a hybrid model. You will manage Snowflake environments, build scalable ELT pipelines, and implement security controls across cloud and on‑prem sources.

You will design, monitor, and optimize data workloads, develop CI/CD pipelines, and collaborate with analytics and engineering teams to drive cost efficiency and governance.