Top Tech Jobs & Startup Jobs

Build reusable data modernization accelerators, frameworks, validation harnesses, and playbook content. Generalize client-specific code for delivery teams, support onboarding, and contribute to migration planning, data validation, reconciliation, parallel runs, and cutover execution across legacy-to-modern cloud platform programs.

Designs enterprise Databricks lakehouse architectures and Delta data models for legacy-platform modernization. Defines migration, validation, reconciliation, parallel-run, and cutover strategies while establishing governance, orchestration, and performance standards. Leads client architecture reviews, guides build teams hands-on, applies AI-assisted conversion approaches, and tunes Spark workloads for scale and cost. The role requires extensive data engineering and architecture experience, including enterprise Databricks implementations and multi-cloud modernization programs.

Designs, develops, and executes automated UI, API, integration, backend, functional, and performance tests. Maintains test plans, cases, frameworks, regression coverage, and testing utilities; analyzes results and defects; and supports manual validation when needed. Collaborates with developers and QA engineers in Agile/Scrum teams, manages defects in JIRA, tests cloud and distributed applications, and integrates automation into CI/CD pipelines.

Lead the design, development, deployment, and optimization of production AI and machine learning systems. Manage end-to-end model lifecycles, collaborate with data science, engineering, and product teams, and ensure model robustness, fairness, and explainability. Mentor junior engineers while contributing to AI engineering practices. Work may include LLMs, RAG, agentic AI, computer vision, real-time inference, edge AI, and MLOps infrastructure.

Identify technical training needs; design and deliver e-learning, workshops, and seminars on cloud, AI applications, and data analytics. Evaluate training effectiveness, manage LMS records, report learning outcomes, support technical onboarding, collaborate with SMEs and vendors, and keep curricula current with technology advancements.

Develop and maintain frontend and backend components of the Hickory application. Build React and NextJS interfaces, backend services, APIs, user management workflows, provisioning automation, data mapping functionality, and cloud integrations. Implement secure, scalable code while working with databases, authentication, authorization, and Azure services.

Designs and maintains data pipelines using ETL/ELT platforms, develops dbt models, and manages Snowflake workloads. Establishes data quality testing and monitoring, optimizes data performance and costs, supports CI/CD and infrastructure-as-code practices, participates in architecture reviews, and mentors junior engineers. Collaborates with analysts and data scientists to build reliable data models and transformation logic.

Build and manage data structures using advanced SQL, stored procedures, tables, views, and Snowflake tools. Analyze complex data relationships, support data governance and quality initiatives, and derive actionable insights. Collaborate with technical and non-technical stakeholders, communicate progress, meet deadlines, and work independently. Preferred experience includes healthcare or financial data, reporting dashboards, data governance documentation, ELT tools, and workflow orchestration platforms.

Lead end-to-end delivery of an enterprise cloud data and AI platform. Design data architectures, ingestion pipelines, models, and machine-learning systems; productionize supervised, unsupervised, deep-learning, and generative AI solutions; establish MLOps, explainability, monitoring, and CI/CD practices; and lead distributed engineering teams. Serve as the primary client-facing technical liaison, driving architecture, governance, documentation, UAT, cutover, and production readiness.

Lead development of production agentic AI applications, translating business outcomes into agent specifications, tools, evaluations, and acceptance criteria. Build retrieval, orchestration, structured-output, approval, fallback, and failure-handling workflows using LLMs and APIs. Own evaluation harnesses, lead agile ceremonies, estimate work, and create sprint plans. Develop applications with Python or Java/Spring Boot and modern front-end technologies, while providing technical leadership and client-ready communication.