Senior Data Platform Engineer

Job summary

We are looking for a Senior Data Platform Engineer to design, build, and operate the foundational data and ML infrastructure that powers analytics, reporting, and machine learning across DigiCert. This role sits at the intersection of data engineering and ML platform work — you will own the systems, pipelines, and tooling that data scientists, analysts, and engineers rely on every day. You bring deep expertise in Databricks, a strong engineering mindset, and hands-on experience building and maintaining ML pipelines in production. You will partner closely with data science, analytics, product, and business teams to deliver a platform that is reliable, governed, and built to scale.

What you will do

• Design, build, and maintain scalable data and ML pipelines using Python and SQL, processing large-scale datasets across batch and streaming workloads
• Own and evolve core platform infrastructure on Databricks — including Delta Lake table architecture, Unity Catalog governance, Databricks Workflows orchestration, and compute optimization
• Build and maintain end-to-end ML pipelines: feature engineering, model training pipelines, experiment tracking (MLflow), and model deployment/serving infrastructure
• Collaborate with data scientists to operationalize models — bridging the gap between experimentation and production-grade ML systems
• Define and enforce data platform standards: ingestion patterns, data modeling conventions, medallion architecture (Bronze/Silver/Gold), and pipeline reliability practices
• Implement data quality, observability, and monitoring frameworks to ensure platform health and data trustworthiness
• Optimize pipelines for performance, cost, and reliability at scale using Spark and