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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.
विवरण
- 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
आवश्यकताएँ
- 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
लाभ
- 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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