Senior Software Engineer, Data Platform

Key Responsibilities

• Contribute to the design, development, and scaling of core data infrastructure using GCP, Spark, Databricks, and Fivetran
• Develop robust and maintainable ETL/ELT workflows that support diverse structured and unstructured data needs
• Implement and manage Change Data Capture (CDC) pipelines to enable near real-time data replication and synchronization
• Define and enforce data governance and compliance standards, including access control, auditability, lineage, and metadata management
• Build and manage streaming and batch data pipelines to serve high-impact use cases across analytics, product, compliance, and experimentation
• Act as a strategic partner to cross-functional teams (product, analytics, engineering, clinical) to ensure data is accessible, trustworthy, and impactful
• Drive the long-term architectural vision of the data platform to support current and future business and product needs

Requirements

• 5+ years of experience in software engineering, with a focus on scalable data architectures
• Strong expertise in GCP (IAM, GCS, Pub/Sub, etc.) and hands-on experience with Spark and Databricks
• Hands-on experience with CDC technologies like Fivetran, or equivalent
• Proficiency in ETL/ELT tools and frameworks (dbt, Apache Airflow, Dataform, etc.)
• Deep understanding of data governance principles, including compliance and security best practices
• Demonstrated success in collaborating across functions to deliver data solutions for analytics, experimentation, or compliance
• Balance of IC execution and leadership skills; comfortable rolling up sleeves or mentoring others
• Familiarity with streaming data architecture, real-time ingestion, and delivery frameworks
• Proficient in SQL and Python for data processing and automation
• Strong problem-solving skills with the ability to work in a fast-paced environment
• Excellent communication and technical storytelling skills

Nice-to-Haves

• Experience with Terraform or Infrastructure-as-Code (IaC) for data infrastructure automation
• Background in HIPAA or other regulated environments with sensitivity to data privacy and compliance
• Familiarity with the dbt Semantic Layer and modern data modeling best practices
• Exposure to data observability platforms and practices
• Familiarity with machine learning data pipelines
• Exposure to multi-cloud or hybrid-cloud environments
• Experience building scalable solutions in a 0-1 environment