Design and build scalable data pipelines using PySpark on Databricks, migrate ETL systems, and develop analytics dashboards and Python applications.

Lead reverse-engineering and modernization of legacy .NET monoliths and n-tier applications. Extract undocumented business logic and data dependencies, produce current-state architecture and data flow models, identify technical debt and risks, design target architectures (including microservices), define migration strategies, support refactoring and data migration, and translate findings for technical and non-technical stakeholders.

Lead assessment and redesign of a legacy data ecosystem into a scalable data lake/lakehouse. Define target-state architecture, canonical models, governance, validation, lineage, and a phased migration roadmap to stabilize downstream batch processing and enable partner onboarding.

Lead the redesign of an Order Management System, driving strategy, architecture, and delivery with a focus on performance and stakeholder management.

Looking for a Senior QA Automation Engineer to lead automated testing, integrate with CI/CD, and ensure quality using various testing frameworks and tools.

Lead large-scale IT operations transformation programs, managing execution and governance, focusing on cloud infrastructure and modern IT practices.

Lead the modernization of legacy data platforms by driving automation, migrating data pipelines from Informatica to Databricks, and establishing governance frameworks.

Design, develop, and enhance solutions on Microsoft Dynamics CRM and Dynamics 365, mentor team members, and support complex enterprise systems.

The Senior IT Infrastructure & Operations Analyst supports large-scale enterprise IT environments, focusing on infrastructure stability and modernization. Responsibilities include operational support, acting as an escalation point, managing backups, and providing mentorship to junior staff.

The Senior Data Architect will lead automation-driven modernization of data and reporting workloads, focusing on scalable architecture and reducing manual effort.

The AI Engineer role focuses on building scalable data pipelines and enabling ML systems in a cloud-native environment, transforming healthcare data infrastructure.

The AI Engineer will design and develop AI-enabled healthcare applications using Java and React, integrate machine learning models, and work on both frontend and backend systems in a microservices architecture.