Top Tech Jobs & Startup Jobs

Develop and maintain Java web applications and RESTful APIs using Spring, microservices, cloud-native practices, and secure coding standards. Build containerized applications, CI/CD pipelines, automated tests, database solutions, and modern front-end interfaces. Collaborate in Agile teams, participate in design and code reviews, troubleshoot production issues, optimize performance, and support global applications. The role also involves application security, cloud deployment, data management, and occasional off-hours production support.

Leads an engineering team delivering secure, scalable .NET applications and RESTful APIs. Oversees solution implementation, cloud deployment across GCP and Azure, Docker containerization, CI/CD, application security, database performance, automated testing, documentation, and compliance. Manages engineer performance and development, coordinates with product and architecture stakeholders, evaluates technologies and vendors, and provides project and team updates to leadership and clients.

Leads a cross-functional analytics team delivering sales, marketing, customer, and business performance insights. Manages people and projects, develops dashboards and reports, analyzes KPIs and campaign effectiveness, and translates complex data into recommendations for leadership and clients. The role involves querying and modeling large datasets, automating analytics processes, building customer profiles and forecasting models, and using AI-powered tools to improve efficiency and business outcomes.

Design, develop, and maintain web applications using Microsoft .NET; design databases and ETL; write code, tests, and documentation; mentor junior developers; perform code reviews, integration testing, and production support; coordinate small projects with PM, QA, and infrastructure teams.

The Senior Data Engineer designs and maintains production data pipelines on GCP using BigQuery, Dataform, Airflow, Dataflow, and Cloud Run. They own data validation, cleansing, troubleshooting, API integrations, and reliable datasets for analytics and AI/ML. The role also involves translating client requirements into data solutions, maintaining dashboards, supporting ad hoc requests, and applying Git, code reviews, and CI/CD practices.

Develops analytical deliverables, business and marketing performance reports, dashboards, and data visualizations. Queries and transforms large datasets, conducts customer and campaign analysis, automates data processes, and provides actionable insights for strategic decisions. Collaborates with clients and cross-functional stakeholders, presents findings, and serves as a subject matter expert in customer analytics, program effectiveness, and financial reporting.

Leads technical delivery for website, web services, database, and interactive technology projects. Manages onshore and offshore development teams, defines client requirements, troubleshoots and deploys code, supports architecture and security initiatives, coordinates technical schedules and priorities, contributes to staffing and pricing, and develops project functionality. Requires hands-on data engineering and application development experience with Python, SQL, databases, Databricks, and cloud platforms.

Develop and deploy AI, generative AI, and LLM solutions that support credit risk modelers. Build and validate credit risk models using GCP, SAS, R, and Python; apply statistical and machine learning techniques; analyze results; document modeling processes; support model development; conduct ad hoc analytics; and implement secure, governed AI tools for analytical workflows.

Lead strategic relationships across a portfolio of enterprise accounts, serving as executive partner and sponsor. Own account strategy, client retention, revenue growth, renewals, forecasting, expansion planning, commercial negotiations, and quarterly business reviews. Coordinate analytics, technology, strategy, activation, and delivery teams to align solutions with client objectives, manage risks, and demonstrate measurable business outcomes.

Leads OneMagnify’s AI practice by guiding client strategy, directing generative AI architecture and delivery, and translating business needs into production-ready solutions. Manages and mentors data scientists, AI engineers, and software engineers while overseeing Databricks-based data pipelines, model deployment, MLOps, and LLM applications. Partners across analytics, strategy, engineering, creative, and operations teams, presents technical concepts to executives, and contributes to evolving the company’s AI service offerings.