Senior/ Lead Platform Engineer (Databricks) job opportunity at TymeX.

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Date2025-10-24T09:20:41.382Z bot
TymeX Senior/ Lead Platform Engineer (Databricks)
Experience: 7-years
Pattern: Full-time
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loacation Ho Chi Minh City, Vietnam
loacation Ho Chi Minh Ci..........Vietnam
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Role Overview  We are seeking a  Senior/Lead Platform Engineer  who will take ownership of the design, implementation and operation of our core data, analytics and ML infrastructure. This role spans across  platform architecture, DevSecOps, DataOps, and ML infrastructure , and requires a combination of strategic thought leadership and hands-on execution. You will build, integrate and operate platforms on  AWS and Databricks , enabling scalable, secure, production-grade ML/AI solutions.  Key Responsibilities  Architect and implement end-to-end data and ML platforms: data lakes, warehouses, streaming and batch pipelines, model training/deployment infrastructure, on AWS + Databricks.  Lead DevSecOps and DataOps practices: infrastructure as code (IaC), CI/CD pipelines for data & ML workflows, secure multi-account/multi-region cloud operations.  Integrate AWS services (e.g., S3, Redshift, Kinesis, Lambda, EKS/ECS) with Databricks runtime, Delta Lake, Unity Catalog etc to build scalable, performant pipelines.  Build and operate ML infrastructure: training clusters, model versioning, MLOps toolchain (e.g., MLflow), model monitoring and observability, automatic retraining workflows.  Establish data governance, lineage, quality, observability standards across data pipelines and ML workflows.  Mentor engineering teams, define architectural best practices and guide implementation of high-scale data/ML systems.  Optimize system performance, cost and scalability; diagnose and resolve large-scale production issues.  Continuously evaluate new tools and technologies in the areas of cloud, data platform, DevSecOps, ML infrastructure and apply them to drive innovation.  7+ years of experience in data platform architecture, cloud/ML infrastructure engineering or related roles.  Deep technical expertise in  Databricks and AWS : demonstrated ability to design, integrate and operate solutions spanning both platforms.  Strong hands-on implementation skills: you will not just design but build, deploy and operate the platform.  Proven track record of building and operating scalable ML/AI platforms in production (model training & deployment).  Expertise in Apache Spark, Delta Lake, modern data pipeline frameworks (batch + streaming).  Strong background in infrastructure as code (Terraform, CloudFormation), CI/CD for data/ML, and DevSecOps practices.  Proficiency in Python and SQL; familiarity with Scala or equivalent is a plus.  Experience with data governance, data lineage, observability and MLOps frameworks (e.g., MLflow, Airflow, dbt).  Bonus: Experience in fintech, regulated industries or high-security environments. 

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