
501 - 1000 employees
Founded 2003
🤝 B2B
🏢 Enterprise
🤖 Artificial Intelligence
B2B • Enterprise • Artificial Intelligence
KANINI is a global digital engineering and IT services firm that helps enterprises transform through product engineering, cloud enablement, data analytics & AI, intelligent automation, and ServiceNow solutions. It builds cloud-native applications, modernizes legacy systems, implements AI/ML and data platforms, and delivers managed outcomes via flexible engagement models for clients across healthcare, banking, energy, government and technology sectors.
🔥 0 minutes ago
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501 - 1000 employees
Founded 2003
🤝 B2B
🏢 Enterprise
🤖 Artificial Intelligence
B2B • Enterprise • Artificial Intelligence
KANINI is a global digital engineering and IT services firm that helps enterprises transform through product engineering, cloud enablement, data analytics & AI, intelligent automation, and ServiceNow solutions. It builds cloud-native applications, modernizes legacy systems, implements AI/ML and data platforms, and delivers managed outcomes via flexible engagement models for clients across healthcare, banking, energy, government and technology sectors.
• Design, develop, and maintain scalable batch and real-time data pipelines on GCP • Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data processing • Build high-performance data transformations using Python and PySpark • Develop and optimize complex SQL queries for analytical workloads • Work extensively with BigQuery for large-scale data processing and performance tuning • Develop and deploy pipelines using Cloud Dataflow • Orchestrate workflows using Cloud Composer (Apache Airflow) • Manage data storage and lifecycle using Google Cloud Storage (GCS) • Implement version control and CI/CD pipelines using Git-based tools • Ensure data security, governance, and access control using GCP IAM • Optimize data solutions for performance, scalability, reliability, and cost-efficiency
• Strong hands-on experience with Google Cloud Platform (GCP) • Expertise in BigQuery (partitioning, clustering, query optimization) • Proven experience implementing Medallion Data Architecture • Strong programming skills in Python and PySpark • Hands-on exposure on Java • Advanced proficiency in SQL (complex joins, window functions, performance tuning) • Hands-on experience with Cloud Dataflow • Experience with Cloud Composer (Airflow) for orchestration • Experience working with Google Cloud Storage (GCS) • Knowledge of version control systems (Git) and CI/CD practices • Strong understanding of GCP IAM and cloud security best practices
• Health insurance • Flexible work arrangements
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