Top Tech Jobs & Startup Jobs

Develop and support Java backend applications and advanced APIs using Spring Boot, microservices, databases, and cloud-native tools. Responsibilities include production incident troubleshooting, vulnerability management, monitoring and observability, authentication and authorization, API management, CI/CD, and Agile Scrum collaboration. The role requires strong communication, teamwork, client focus, and the ability to mentor others. Candidates need a bachelor’s degree and at least seven years of software engineering and API development experience.

Analyze and redesign fraud prevention and detection processes for banks and insurers. Translate regulatory and business needs into functional requirements, user stories, process designs, and real-time fraud decisioning solutions. Support payment journeys, fraud data and behavioral analytics, operating models, case management, and customer protection initiatives. Facilitate cross-functional workshops and provide actionable recommendations across Fraud, Risk, Payments, Operations, IT, Compliance, and Customer Experience.

Develop and improve Java/J2EE applications, including performance tuning and process improvement. Train junior team members, provide technical solutions, and contribute to full-stack development using Java, Spring, Hibernate, Angular, JDBC, SQL, and web technologies. Collaborate with teams, apply Agile and test-driven development practices, and support efficient continuous integration and delivery.

Implement and maintain data governance frameworks, policies, standards, and data quality controls. Manage data ownership, stewardship, metadata, lineage, and issue remediation processes. Partner with business, technology, risk, and compliance stakeholders, facilitate governance forums and training, and support audits, regulatory initiatives, and enterprise data transformation programs for banking clients.

Design, develop, and optimize data architectures for agile financial-services projects. Responsibilities include data engineering, business analysis, solution design, conceptual data modeling, and implementation of data lakes, warehouses, and cloud-based solutions. The role involves progressively owning project topics, leading smaller workstreams and teams, and contributing to internal initiatives.

Design and implement enterprise data architectures and cloud data foundations for financial-services transformation projects. Lead data modeling, integration, ETL/ELT, governance, source onboarding, legacy migration, and architecture workstreams using Azure Databricks. Collaborate with business, engineering, governance, and operations teams while documenting solutions, guiding engineers, and transferring capabilities into production operations.

Design and implement enterprise data architectures for regulated financial-services clients. Build Azure Databricks cloud foundations, onboard data sources, develop enterprise models, establish ETL/ELT and governance patterns, guide legacy migrations, lead architecture workstreams, and collaborate with business, engineering, governance, and operations teams. Support AI, analytics, reporting, documentation, and knowledge transfer into operations.

Designs agentic AI architectures and technical roadmaps for financial services clients. Translates business and technical requirements into scalable AI platforms, memory architectures, multi-agent systems, tool workbenches, and implementation requirements. Advises C-suite stakeholders, oversees AgentOps tracing and monitoring, establishes AI governance and security guardrails, and creates reusable architectures and methodologies. Collaborates across business, IT, risk, compliance, and consulting teams.

Design and implement enterprise data architectures for regulated financial-services clients. Build Azure Databricks cloud data foundations, onboard sources, develop enterprise data models, and establish ETL, ELT, API, governance, security, metadata, lineage, and data-quality patterns. Lead architecture decisions, migration workstreams, and project teams while collaborating with business, engineering, governance, and operations stakeholders. Support documentation, knowledge transfer, and transition into operations.

Design, develop, and optimize data architectures for agile financial-services projects. Perform data engineering, business analysis, solution design, data modeling, and technical implementation using cloud, data lake, data warehouse, and database technologies. Progressively own technical topics, lead smaller workstreams and teams, and contribute to internal initiatives and solution improvements.