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Carelon Global Solutions Philippines
Carelon Global Solutions Philippines
5.001 – 10.000 Angajați
AsigurăriConsultanțăLogistică
Carelon Global Solutions Philippines sprijină organizațiile din domeniul sănătății prin îmbunătățirea modului practic și eficient de furnizare a operațiunilor și serviciilor. În calitate de filială a Elevance Health, cunoscută anterior sub numele de Legato Health Technologies, compania dezvoltă instrumente digitale și soluții operaționale pentru planuri de sănătate, furnizori de servicii medicale și sisteme de sănătate. Forța sa de muncă globală, formată din peste 25.000 de angajați, se întinde în Statele Unite, India, Irlanda, Filipine și Puerto Rico. Compania caută abordări inovatoare care să îi ajute pe profesioniștii din domeniul sănătății să reducă efortul administrativ și să se concentreze mai mult asupra îngrijirii pacienților, punând în același timp accent pe mentorat și dezvoltarea carierei angajaților.
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Locurile de muncă ale companiei

Tech Lead II, Databricks – Bengaluru Onsite

Lead Databricks, Snowflake, and cloud data engineering for Carelon Global Solutions’ healthcare platforms. Build scalable lakehouse pipelines and guide modernization initiatives across India-based teams.

INIndiaLa sediuNormă întreagăSeniorLimbă Obligatorie: englezăInginer full-stackInginer software
ApacheAWSAzureCloudDockerETLGoogle Cloud PlatformJenkinsKafkaKubernetesPySparkPythonSparkSQLTerraformUnity

Descriere

  • Own the delivery of scalable data engineering solutions
  • Lead end-to-end pipeline development with Databricks and Python
  • Design frameworks for both batch and real-time data processing
  • Review implementation quality and define engineering standards
  • Coach teams on performance tuning and system reliability
  • Develop and support ETL/ELT pipelines with Databricks, Spark, and Python
  • Create scalable lakehouse architectures
  • Establish data quality, governance, and observability practices
  • Tune Snowflake workloads and refine data models
  • Design Iceberg-based data lakes for large-scale analytics
  • Use AWS and GCP cloud services
  • Build cloud-native solutions with managed services
  • Contribute to platform modernization and cloud migration efforts
  • Collaborate with architects, product owners, and business stakeholders
  • Convert business needs into practical technical designs
  • Estimate work and support delivery planning

Cerințe

  • B.Tech or MCA in computer science, or equivalent professional experience
  • At least 7 years of overall experience
  • At least 3 years of relevant Databricks experience
  • Practical experience designing and delivering scalable Databricks lakehouse solutions
  • Advanced Python and PySpark skills
  • Deep Snowflake experience covering data modeling, performance tuning, query optimization, and cost control
  • Hands-on knowledge of Apache Iceberg, Delta Lake, and modern open table formats
  • Strong knowledge of AWS or GCP services, architecture, deployment, and platform operations
  • Experience creating batch and real-time pipelines with Spark, Kafka, and cloud-native services
  • Expertise in ETL/ELT architecture, data integration, and cloud migration
  • Experience leading engineering teams and delivering data modernization programs
  • Strong analytical and troubleshooting abilities
  • Excellent communication and stakeholder management skills
  • Expert knowledge of Databricks Lakehouse Architecture, Delta Lake, Unity Catalog, Workflows, and performance optimization
  • Strong command of Spark SQL and distributed processing
  • Extensive hands-on knowledge of Snowpipe, Streams, Tasks, data sharing, and query optimization
  • Advanced Apache Iceberg knowledge, including schema evolution, partitioning, and time travel
  • Experience designing and delivering large-scale data engineering and ETL/ELT pipelines
  • Hands-on experience with AWS, Azure, or GCP cloud-native data services
  • Strong SQL and data modeling capabilities across OLTP and analytical systems
  • Experience processing real-time data with Kafka, Event Hubs, Kinesis, or Pub/Sub
  • Knowledge of data governance, metadata management, data quality, and security frameworks
  • Preferred: Terraform, CloudFormation, or other infrastructure-as-code tools
  • Preferred: Docker, Kubernetes, and containerized data platforms
  • Preferred: CI/CD tools such as GitHub Actions, Jenkins, Azure DevOps, or GitLab
  • Preferred: AI/ML, MLOps, and GenAI data platform integration
  • Preferred: Data Mesh, Data Fabric, and modern enterprise data architecture
  • Preferred: Databricks, Snowflake, or cloud platform certifications

Beneficii

  • Strong investment in learning and professional development
  • An innovative and creative culture with room for autonomy
  • Programs supporting holistic well-being
  • Diversity, equity, and inclusion initiatives
  • Multiple avenues for rewards and recognition
  • Competitive health and medical insurance
  • High-quality amenities and workplace facilities
  • Associate-centered workplace policies

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