Senior/Lead Platform Engineer (Databricks, MLops, AWS)
Core
Design, implement, and operate core data, analytics, and ML infrastructure on AWS and Databricks to enable scalable, secure, production-grade ML/AI solutions.
Role type
Senior/Lead Platform Engineer (Data & ML Infrastructure)
Builds
End-to-end data and ML platforms including data lakes, warehouses, streaming/batch pipelines, and model training/deployment infrastructure.
Domain
Cloud infrastructure, Data Engineering, Machine Learning Operations (MLOps)
Deliverable
production ML models | infrastructure
Required skills
AWS services (S3, Redshift, Kinesis, Lambda, EKS/ECS), Databricks, Apache Spark, Delta Lake, Infrastructure as Code (Terraform, CloudFormation), CI/CD for data/ML, Python, SQL, MLOps toolchains (MLflow, Airflow, dbt), data governance and lineage, observability.
Preferred skills
Scala, experience in fintech or regulated industries, high-security environments.
Responsibilities
Architect and implement end-to-end data and ML platforms; lead DevSecOps and DataOps practices; integrate AWS services with Databricks runtime; build and operate ML infrastructure including training clusters and model monitoring; establish data governance and quality standards; mentor engineering teams and define architectural best practices; optimize system performance, cost, and scalability.
Seniority
Senior/Lead, hands-on IC with strategic thought leadership
