Lead the development, optimization, and scaling of production-grade data ingestion and transformation pipelines. Ensure data correctness and operational reliability across AWS, Snowflake, and event-driven architectures.
Nexaminds
21 Remote Job Openings at Nexaminds
Lead the design and development of reusable, config-driven data ingestion engines and transformation pipelines using Python and Azure Databricks. Implement metadata-driven validation layers and optimize Spark jobs to scale data solutions across various healthcare data domains.
Design and maintain scalable backend microservices using C# and .NET while building full-stack applications with Angular and React. Lead modernization initiatives and mentor engineers on best practices like Clean Code and CI/CD.
Design and maintain scalable backend services using C# and .NET while building modern frontend applications with React. Integrate AI-powered capabilities and cloud-native solutions into high-performance applications.
Design and maintain scalable automation solutions and AI-powered workflows to improve operational efficiency. Automate provisioning, monitoring, and remediation across network, cloud, and security environments.
Install, configure, and maintain database environments across production, development, and disaster recovery systems. Ensure high availability and optimal performance through query optimization, tuning, and security implementation.
Design, develop, and optimize scalable data pipelines and integration solutions using Databricks, Python, and SQL. Manage cloud-based data infrastructure on Azure and ensure data quality through profiling and validation.
Design, build, and maintain scalable data pipelines and optimize ETL/ELT processes for performance and cost efficiency. Collaborate with stakeholders to define data requirements and implement best practices for data governance and security.
Design, build, and maintain scalable data pipelines using Databricks, Python, and Spark. Optimize ETL/ELT processes and implement best practices for data quality, governance, and security.
Lead and develop a team of principal-level engineers while managing delivery visibility and dependencies for a large-scale modernization program. Act as a coordination layer between engineering teams and senior leadership to ensure alignment with program standards and remove organizational friction.
Lead a high-impact team focused on internal developer platforms and productivity while contributing hands-on to architecture and coding. Manage the technical roadmap, mentor engineers, and drive the adoption of AI-assisted development tools across the organization.
Lead a high-impact team focused on internal developer platforms and productivity while contributing hands-on to architecture and coding. Manage the technical roadmap, mentor engineers, and drive the adoption of AI-assisted development tools.
Lead the modernization of a monolithic enterprise platform by designing distributed data models and migration strategies from SQL Server to Azure Cosmos DB. Define event schema standards and data ownership models to enable a seamless transition to a cloud-native microservices architecture.
Design and implement scalable Azure Cosmos DB solutions, focusing on data modeling, performance optimization, and cost management. Lead the migration of relational databases from SQL Server to Cosmos DB and support event-driven architectures.
Design and implement scalable APIs and production-ready agentic solutions using Go. Collaborate with stakeholders and cross-functional teams to translate business needs into technical requirements and high-quality backend architectures.
Lead the development, optimization, and scaling of data solutions by building end-to-end pipelines on Databricks. Design reusable ingestion engines and implement transformation components for batch and streaming data using a medallion architecture.
Design, develop, and deploy scalable backend services and microservices using Java, Python, and GCP. Build reliable data pipelines and support the integration of Large Language Models and AI-powered services.
Lead the development, optimization, and scaling of data solutions by building reusable ingestion engines and transformation components. Implement metadata-driven validation layers and maintain production-ready onboarding templates for various data domains.
Lead the design and development of scalable cloud-native backend solutions and secure microservices using Java, Python, and GCP. Provide technical leadership by mentoring engineers, conducting design reviews, and managing the application security posture.
Design, build, and scale high-performance backend systems, microservices, and data pipelines using Java, Python, and GCP. Ensure application safety by remediating security vulnerabilities and maintaining high code quality through reviews and documentation.
Design and deploy scalable backend services, APIs, and data pipelines using Java, Python, and GCP. Support the integration of Large Language Models and AI-powered services while maintaining high code quality and security.
