Top Tech Jobs & Startup Jobs

Build and maintain scalable data pipelines, ETL/ELT processes, data models, metric definitions, and data infrastructure. Develop production solutions with Python, SQL, Spark, dbt, Fivetran, Airflow, Databricks, Azure, and cloud storage. Collaborate with data scientists, engineers, analysts, and stakeholders to deliver reliable, accessible data and self-service tools. Troubleshoot pipeline issues, improve data quality and scalability, and use AI-assisted development tools to accelerate engineering work.

Build and enhance data engineering frameworks, scalable data solutions, centralized ETL logic, metric definitions, and concise data models. Develop self-service data tools supporting data science, internal applications, and organizational decision-making. Collaborate with cross-functional stakeholders, use AI coding agents such as Claude Code or Codex, and write production-level Python and SQL.

Designs and maintains CI/CD pipelines, automates cloud infrastructure with IaC, manages Kubernetes and GCP/GKE environments, and implements progressive delivery, observability, alerting, and incident response. The role partners with Engineering, QA, and Product teams to improve reliability, scalability, security, deployment velocity, and operational efficiency while troubleshooting production issues and promoting DevOps, SRE, and GitOps practices.

Leads end-to-end technology projects in healthcare, coordinating Engineering, Product, QA, Infrastructure, and business teams. Manages project plans, timelines, budgets, risks, dependencies, resources, stakeholder communications, Agile ceremonies, governance, compliance, and delivery quality. Drives issue resolution, executive reporting, and continuous improvement across multiple concurrent initiatives.

Build and support scalable healthcare data platforms, unified data models, datasets, and ad hoc data access solutions. Extract and integrate heterogeneous healthcare data, improve data quality, support acquisitions, and model data for BI, software applications, machine learning, and AI. Collaborate with product, engineering, business, and clinical stakeholders while following software development lifecycle best practices.

Design, build, deploy, and scale Python-first backend services, REST APIs, data pipelines, and cloud-native applications on GCP. Maintain and enhance Java services, integrate AI and LLM capabilities, modernize infrastructure, and ensure application security, reliability, and high test coverage. Collaborate with product, data, and infrastructure teams while conducting code reviews and documenting technical solutions.

Lead end-to-end technology projects in healthcare from planning through implementation. Coordinate Engineering, Product, QA, Infrastructure, and business teams; manage schedules, budgets, resources, risks, dependencies, and stakeholder communications; facilitate Agile ceremonies; ensure quality, compliance, documentation, and successful delivery; and drive continuous improvements across project processes and collaboration.

Design, develop, test, and maintain native iOS applications using Swift. Integrate RESTful APIs, collaborate with Java backend and React web teams, and contribute to architecture, code reviews, Agile planning, testing, CI/CD, and App Store releases. Troubleshoot performance, stability, and production issues while improving application quality and maintainability. Communicate technical progress and tradeoffs with cross-functional stakeholders.

Design, develop, and maintain native Android applications using Kotlin and Android Studio. Integrate mobile apps with RESTful APIs and backend services, collaborate with Java backend and React teams, troubleshoot production issues, participate in architecture discussions and code reviews, support releases and CI/CD improvements, and communicate technical progress and tradeoffs.

Principal Data Engineer responsible for developing and supporting Databricks pipelines, integrating heterogeneous healthcare data sources, modeling unified data products, and ensuring data quality and availability. The role partners with business stakeholders, product teams, data engineers, and clinical leaders to gather requirements, create datasets, support ad hoc analytics, enable machine learning and AI use cases, and assist with acquisition integrations. Extensive healthcare data, cloud, SQL, PySpark, and Python experience is required.