Senior Data Platform Engineer

About the role

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.

Key responsibilities

• Design, build, and maintain scalable data and ML pipelines using Python and SQL for batch and streaming workloads.
• Own and evolve core platform infrastructure on Databricks, including Delta Lake architecture, Unity Catalog governance, and Databricks Workflows.
• Build end‑to‑end ML pipelines: feature engineering, model training, experiment tracking with MLflow, and model deployment.
• Define and enforce data platform standards such as medallion architecture (Bronze/Silver/Gold) and ingestion patterns.
• Implement data quality, observability, and monitoring frameworks to ensure platform health.

Required profile

• 6+ years of experience in data engineering, data platform, or ML engineering.
• Strong proficiency in Python and SQL with production‑grade pipeline experience.
• Hands‑on expertise with Databricks ecosystem (Delta Lake, Unity Catalog, Workflows, PySpark).
• Experience building and maintaining ML pipelines in production, including model deployment.
• Familiarity with cloud data platforms (AWS, Azure, or GCP) and CI/CD practices.

Required skills

• Python
• SQL
• Databricks (Delta Lake, Unity Catalog, Workflows)
• PySpark / Spark
• MLflow
• Cloud platforms: AWS, Azure, GCP
• Git and CI/CD for data/ML workflows

What we offer

• Generous time‑off policies
• Top‑shelf benefits
• Education, wellness and lifestyle support