Senior Software Engineer, Data & AI Platform
$179,400–$224,300 year
Remote
Job Summary
Design and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance. Develop reusable abstractions, templates, services, and workflows that standardize data pipelines and products. Partner with Analytics, Applied-AI, Data-engineering, and application teams to deliver platform capabilities supporting business and clinical decision-making. Evaluate modern data and AI technologies focusing on scalability, reliability, developer experience, and cost efficiency. Apply Generative AI to improve data enablement, documentation, discovery, workflow automation, and platform usability. Promote software engineering best practices including clean code, automated testing, CI/CD, infrastructure-as-code, monitoring, and secure data handling. This role requires 5+ years of experience in scalable data platforms and hands-on skills in Python, SQL, Spark, Kubernetes, and Terraform. Salary ranges from $156,000 to $224,300 depending on geographic zone.
Required Qualifications
- 5+ years of professional software engineering or data engineering experience building scalable data platforms, services, pipelines, or analytics infrastructure
- Hands-on experience with modern data architectures, including data lakes, lakehouses, warehouses, analytical datastores, and batch or real-time processing systems
- Strong programming skills in Python and SQL, with experience building production-grade data systems
- Working knowledge of distributed computing and cloud-native technologies such as Spark, Kubernetes etc
- Hands-on experience with Infrastructure as Code using Terraform (or a similar tool such as Pulumi, CloudFormation/CDK) to provision and manage cloud infrastructure
- Experience applying data engineering best practices around data quality, lineage, governance, reliability, observability, and operational excellence
- Practical experience using Generative AI tools or technologies to improve engineering workflows, automation, analytics, or data platform capabilities
- Strong problem-solving, communication, and collaboration skills, with the ability to work effectively across technical and non-technical teams
- Self-directed, pragmatic, and comfortable working through ambiguity in a fast-moving environment
Desired Qualifications
- Hands-on experience with Databricks, including Delta Lake, Unity Catalog, Workflows, Delta Live Tables, MLflow, Model Serving
- Experience with NoSQL datastores, including document databases, graph databases, key-value stores, wide-column stores, or search-oriented systems
- Experience with Generative AI application patterns such as RAG, knowledge-graph, etc
- Experience working with sensitive data in regulated environments such as healthcare, privacy, fintech, or other compliance-heavy industries
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