Data Platform Engineer

📋 Description

• Platform Architecture: Design core data platform components (Snowflake, Databricks, S3).
• Streaming Infrastructure: Manage high-throughput streaming with Kafka or Kinesis for real-time telemetry.
• Self-Service Enablement: Build Data-as-a-Service features for easy data onboarding and access control.
• Distributed Systems Optimization: Tune Spark and PySpark for performance and cost across large clusters.
• Security & RBAC Architecture: Design granular access controls to meet global compliance (GDPR, CCPA).
• Interoperability & Standards: Ensure data flow between platforms using Iceberg to maintain SSOT.

🎯 Requirements

• Education: Bachelor's or Master's in CS or Engineering or related field.
• Experience: 6+ years in data platform or distributed systems in high-volume environments.
• Core Tech Stack: SQL and Python mastery; Spark expertise.
• Cloud Ecosystem: AWS S3, EKS, IAM, SNS/SQS plus Snowflake or Databricks.
• Orchestration: Experience with Airflow or similar workflow tooling.
• Architecture Mindset: Knowledge of data modeling (Kimball, Inmon, Data Vault) for cloud platforms.

🎁 Benefits

• Great Company Culture: creative, diverse, innovative environment.
• Growth: opportunities to grow within the company.
• Work Hard, Enjoy Life: team events, socials, and office activities.
• Benefits: health and life insurance, 3X CTC coverage, and more.
• Perks: gym reimbursement, wellbeing program, and learning platforms.