Data Engineer - Intermediate

LEAD DATA PLATFORM ENGINEER

Primary Responsibilities:

• Design, implement, and manage cloud infrastructure and platform services across AWS, Datameer, Tableau, MicroStrategy, Snowflake, Airflow etc.
• Build and maintain CI/CD pipelines for data and analytics applications, ensuring reliable and automated deployments.
• Manage infrastructure as code (IaC) using tools such as Terraform or CloudFormation.
• Ensure platform reliability through monitoring, alerting, logging, and incident response practices.
• Optimize performance, scalability, and cost across cloud environments and analytics platforms.
• Implement security best practices, including identity management, data protection, and compliance controls.
• Collaborate with data engineering, analytics and cross-functional teams to enable efficient data workflows and platform usage.
• Automate operational processes to improve efficiency and reduce manual intervention.
• Support environment provisioning, configuration management, and release management processes.
• Contribute to platform governance, including access controls, auditability, and operational standards.
• Provide technical leadership, set platform standards, and mentor engineers contributing to the analytics platform.
• Participate in on-call rotations and lead incident response for platform-related outages.

Basic Qualifications:

• Bachelor’s degree in computer science, engineering, or related field with 5+ years of platform or platform engineering experience.
• Strong experience with Snowflake, MicroStrategy and Tableau platform administrative management & support.
• Strong experience with AWS services such as EC2, S3, Lambda, RDS, CloudWatch, IAM, and VPC.
• Hands-on experience with CI/CD tools such as GitLab CI, Jenkins, or similar.
• Experience with infrastructure as code (Terraform, CloudFormation).
• Experience managing and supporting analytics platforms such as Airflow, Datameer and Tableau.
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Experience with scripting languages such as PySpark, Python, Bash, or similar.
• Familiarity with monitoring and observability tools (CloudWatch, Prometheus, Grafana, etc.).
• Understanding of networking, security, and cloud architecture principles.
• Strong troubleshooting and problem-solving skills.
• Excellent communication skills with the ability to work cross-functionally.

Preferred Qualifications:

• Experience with data platform ecosystems and integration with AWS services
• Familiarity with data pipeline orchestration tools such as Apache Airflow.
• Experience implementing Platform practices for BI and analytics tools, especially MicroStrategy and Tableau.
• Experience with data warehouses like Snowflake or Redshift.
• Knowledge of Datameer platform administration, optimization, and troubleshooting
• Experience with secrets management tools (AWS Secrets Manager, HashiCorp Vault).
• Experience implementing security and compliance frameworks in cloud environments.
• Familiarity with cost optimization strategies for cloud infrastructure.
• Experience working in retail, e-commerce, or consumer-facing environments.
• Exposure to AI/ML platform deployment and MLOps practices.