Senior Software Engineer (Python)

We are seeking an experienced Software Engineer (Senior / Lead) to help architect and scale our Clinical Data Layer —a cloud-native platform designed to harmonize complex clinical trial dataset streams into the standardized CDISC SDTM structure. In this end-to-end engineering position, you will build robust serverless data pipelines alongside the analytical interface tools used by clinical data specialists. Your work directly underpins global regulatory submissions, patient safety monitoring, and key clinical research outcomes. Daily tasks: - Data Pipeline Engineering: Architect and enhance our core SDTM transformation engine, leveraging AWS Step Functions for orchestration, Lambda for compute, and Databricks for high-throughput data processing. - API & Interface Development: Construct and refine responsive React/TypeScript interfaces backed by GraphQL (AWS AppSync) to empower analysts in defining data mapping rules. - Infrastructure as Code (IaC): Maintain, deploy, and scale service-level Terraform stacks and shared cloud resources. - Engineering Excellence: Actively contribute to architectural decisions, perform code reviews, participate in on-call rotations, and mentor junior team members. Essential Requirements: Experience: 5+ years of hands-on software development experience for Senior level (8+ years for Lead level). Python Mastery: Deep proficiency with Python, including clean code architecture, monorepo patterns, and test-driven development ( pytest , pytest-bdd ). AWS Expertise: Proven track record with serverless AWS primitives (Lambda, Step Functions, S3, DynamoDB, IAM), with a clear focus on latency optimization, fault tolerance, and cost efficiency. Strong Advantages: GraphQL & Front-End: Hands-on experience with AWS AppSync schema/resolver development and integration with modern React/TypeScript clients (Vite). Infrastructure Automation: Expertise writing and debugging multi-environment Terraform configurations. Big Data & Analytics: Experience using Databricks or similar distributed data frameworks. Domain & Regulatory Standards: Familiarity with clinical data models ( CDISC SDTM, ADaM ) or software compliance in regulated spaces ( GxP, 21 CFR Part 11 ). Distributed Architecture: Solid understanding of event-driven software patterns (fan-out/fan-in, idempotency, retry strategies). 🛠️ Core Tech Stack Core & Compute: Python, AWS Lambda, AWS Step Functions Data & Storage: Databricks, Amazon DynamoDB, Amazon S3, OpenSearch API & Front-End: AWS AppSync (GraphQL), React, TypeScript, Vite Infrastructure & CI/CD: Terraform, GitHub Actions Must have: Python, Clean Code, Test-driven development, AWS, AWS Lambda, AWS S3, AWS DynamoDB, IAM Nice to have: React, TypeScript, Terraform, Databricks, Data models, GXP