Senior Data Engineer

As a Senior Data Engineer at our company, you will be responsible for designing, building, and operating scalable cloud-native data platforms for global customers. Your role will involve working on modern data architectures, large-scale ETL/ELT systems, streaming pipelines, and AI-driven data platforms using technologies such as Databricks, PySpark, Azure, and Kafka. Here is a detailed overview of what is expected from you: Key Responsibilities: - Modernize legacy and non-scalable data architectures into cloud-native platforms - Design and implement Medallion Architecture (Bronze, Silver, Gold) using Delta Lake and Databricks - Build scalable ETL/ELT pipelines using PySpark, SQL, and Databricks notebooks - Develop and manage workflows using Databricks Workflows / Jobs - Optimize Spark jobs for performance, scalability, and cost efficiency - Implement data quality, governance, and lineage using DLT Expectations and Unity Catalog - Build real-time and event-driven data pipelines using Kafka or similar streaming technologies - Ensure platform reliability through monitoring, observability, and alerting - Collaborate with global customers and cross-functional engineering teams - Participate in architecture reviews, technical design, and best practice implementation Required Skills: - 4+ years of experience in Data Engineering / Big Data Engineering - Strong hands-on experience with Databricks ecosystem - Deep expertise in PySpark and distributed data processing - Experience with Delta Lake, DLT, Unity Catalog, and Databricks Workflows - Strong understanding of ETL/ELT pipelines and data modeling - Experience with Azure Data Platform (ADLS, Azure services) - Experience with Kafka or event-streaming platforms - Good understanding of scalable distributed systems and event-driven architecture - Strong problem-solving and analytical skills - Excellent communication and stakeholder management skills - Experience working with global customers in client-facing environments Good to Have: - Healthcare / HealthTech domain experience - EHR/EMR migration projects - FHIR, HL7, CDA standards - HIPAA compliance exposure - Experience with Patient 360 or Master Patient Index platforms - AI-assisted development tool exposure Joining our team will offer you the opportunity to work on cutting-edge AI and SaaS platforms, exposure to global customers across various regions, high ownership, and a fast growth environment. You will also experience a flexible work culture focused on outcomes and work alongside accomplished global engineering teams, influencing architecture, product, and business outcomes. As a Senior Data Engineer at our company, you will be responsible for designing, building, and operating scalable cloud-native data platforms for global customers. Your role will involve working on modern data architectures, large-scale ETL/ELT systems, streaming pipelines, and AI-driven data platforms using technologies such as Databricks, PySpark, Azure, and Kafka. Here is a detailed overview of what is expected from you: Key Responsibilities: - Modernize legacy and non-scalable data architectures into cloud-native platforms - Design and implement Medallion Architecture (Bronze, Silver, Gold) using Delta Lake and Databricks - Build scalable ETL/ELT pipelines using PySpark, SQL, and Databricks notebooks - Develop and manage workflows using Databricks Workflows / Jobs - Optimize Spark jobs for performance, scalability, and cost efficiency - Implement data quality, governance, and lineage using DLT Expectations and Unity Catalog - Build real-time and event-driven data pipelines using Kafka or similar streaming technologies - Ensure platform reliability through monitoring, observability, and alerting - Collaborate with global customers and cross-functional engineering teams - Participate in architecture reviews, technical design, and best practice implementation Required Skills: - 4+ years of experience in Data Engineering / Big Data Engineering - Strong hands-on experience with Databricks ecosystem - Deep expertise in PySpark and distributed data processing - Experience with Delta Lake, DLT, Unity Catalog, and Databricks Workflows - Strong understanding of ETL/ELT pipelines and data modeling - Experience with Azure Data Platform (ADLS, Azure services) - Experience with Kafka or event-streaming platforms - Good understanding of scalable distributed systems and event-driven architecture - Strong problem-solving and analytical skills - Excellent communication and stakeholder management skills - Experience working with global customers in client-facing environments Good to Have: - Healthcare / HealthTech domain experience - EHR/EMR migration projects - FHIR, HL7, CDA standards - HIPAA compliance exposure - Experience with Patient 360 or Master Patient Index platforms - AI-assisted development tool exposure Joining our team will offer you the opportunity to work on cutting-edge AI and SaaS platforms, exposure to