Top Tech Jobs & Startup Jobs

Build a future-state cloud data platform MVP using Snowflake, dbt, AWS, Fivetran, and Power BI. Responsibilities include developing scalable pipelines, data models, ingestion and transformation workflows, automated testing, quality controls, monitoring, CI/CD, DataOps, governance, metadata management, and security for sensitive healthcare data. The role also supports legacy migration, establishes reusable engineering standards, troubleshoots platform issues, and transfers knowledge to internal teams.

Leads large, complex rewards and transformation projects from setup through delivery. Establishes governance, plans, milestones, workshops, reporting, RAID management, stakeholder communications, vendor coordination, change management, and operational readiness. Requires hands-on rewards program lifecycle experience, including rewards model design, rule changes, optimization, partnership strategy, and onboarding, along with practical Agile delivery expertise.

Provides strategic architecture leadership for an enterprise Databricks data modernization program. Defines target-state data and analytics architectures, migration strategies, governance frameworks, security standards, and implementation roadmaps. Guides engineering teams on scalability, performance, cost optimization, integration, and AI/ML enablement while aligning technology investments with business and regulatory requirements. Engages executives, stakeholders, and vendors; oversees solution quality, mitigates technical risks, and mentors teams.

Design and build scalable cloud-native data platforms, lakehouse architectures, data pipelines, and models using Python, SQL, and major cloud technologies. Modernize legacy environments, deliver client solutions, support pre-sales, and provide technical leadership and mentorship. Responsibilities include technical reviews, automation, infrastructure optimization, stakeholder engagement, knowledge sharing, and contributing to consulting engagements. Senior-level work additionally involves enterprise architecture, data mesh, infrastructure as code, technical strategy, and end-to-end delivery leadership.