Full-Stack Engineer / Data & Analytics (React, Python, AWS)

About the Role We are looking for a Full-Stack Engineer with 6–8 years of experience to build and modernize cloud-based data and analytics applications. This is a hands-on engineering role for someone who can work across modern frontend applications, Python backend services, analytical data, and AWS cloud infrastructure. You will build applications that transform complex business data into secure, interactive dashboards and decision-support experiences. This is not a traditional CRUD application development role. You should be comfortable understanding how data moves from source systems through transformation and API layers to the metrics and visualizations presented to users. What You Will Do Build modern, responsive analytics applications using React and TypeScript. Develop interactive dashboards, charts, KPI views, filters, drilldowns, and data exploration experiences. Build reusable visualization components and metadata-driven interfaces where dashboards and charts can be dynamically configured rather than hardcoded. Develop production-grade REST APIs and backend services using Python and FastAPI. Work with complex business datasets and analytical data models. Write and optimize SQL queries for reporting, metrics, aggregations, and analytical workloads. Work with cloud data warehouses and data-transformation pipelines. Trace metrics from source data through transformation and API layers to the final user-facing visualization. Investigate data discrepancies and ensure consistency between source data, analytical models, APIs, and dashboards. Integrate interactive visualizations using modern charting libraries. Implement secure authentication, authorization, and role-based or row-level data access. Build and deploy applications and supporting services on AWS. Provision and manage cloud infrastructure using Infrastructure as Code. Contribute to CI/CD pipelines, automated testing, monitoring, and production support. Participate in code reviews and technical design discussions. Take substantial features from technical design through implementation, testing, and production deployment. Required Experience 6–8 years of professional software development experience. Strong hands-on experience building production applications with React and TypeScript. Strong experience developing backend services and REST APIs using Python, preferably FastAPI or Flask. Strong SQL skills and experience working with complex, data-intensive applications. Hands-on experience building analytics, reporting, business intelligence, or other data-intensive applications. Experience working with analytical datasets, aggregations, KPIs, metrics, and reporting logic. Experience with analytical or dimensional data models used for reporting and analytics. Experience with at least one cloud data warehouse such as Amazon Redshift, Snowflake, or BigQuery. Experience building interactive dashboards and integrating data visualizations using ECharts, D3.js, Highcharts, Plotly, or similar libraries. Experience building reusable frontend components and responsive web applications. Strong hands-on experience with AWS and cloud-native application deployment. Hands-on experience with Infrastructure as Code using AWS CDK, Terraform, or CloudFormation. Experience with Git-based development, automated testing, and CI/CD practices. Ability to independently own and deliver substantial application features from development through production deployment. Preferred Experience Experience with FastAPI, SQLAlchemy, and Pydantic. Experience with Tailwind CSS or another modern styling framework. Hands-on experience with dbt Core or similar data-transformation frameworks. Experience developing layered data models for analytics, including staging, intermediate, and analytics or mart layers. Familiarity with dimensional modeling concepts, incremental data processing, and slowly changing dimensions. Experience with metadata-driven or configuration-driven application architectures. Experience implementing role-based or row-level data access controls for analytics applications. Experience with AWS services such as ECS/Fargate, RDS, DynamoDB, S3, CloudFront, API Gateway, IAM, and Secrets Manager. Experience with AWS CDK, particularly using Python. Experience building and maintaining CI/CD pipelines using GitHub Actions or similar tooling. Experience modernizing or migrating existing analytics applications while preserving business logic and metric accuracy. Good to Have Exposure to semantic-layer technologies such as MetricFlow, LookML, Cube, or AtScale. Experience working with governed metric definitions or semantic models. Experience integrating Microsoft Entra ID/Azure AD using MSAL or SAML. Experience building Progressive Web Applications or mobile-first interfaces. Experience with monorepo tooling such as Turborepo or Nx. Experience in healthcare, life sciences, commercial analytics, or another data-intensive enterprise domain. Exposure to AI-assisted software development tools, including coding assistants, agentic development tools, or AI-enabled IDEs. Experience using AI tools to improve software development, testing, debugging, code review, or technical documentation. Familiarity with integrating LLM APIs or AI-powered capabilities into applications is a plus but is not required.