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Tiger Analytics Inc.

MLOps Lead Engineer

LocationSt. Louis, Missouri, United States
Typefull-time
SeniorityLead
Experience8+ yrs
DepartmentMLE
Company size5,001–10,000 people
PostedAug 26, 2026 · 1mo ago
Verified live1h ago
At a glanceSummarised by Seekless from the posting.
Must have5
8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations
Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python
Strong experience building automated CI/CD/CT pipelines using Databricks Asset Bundles (DABs), Azure DevOps, or GitHub Actions
Deep understanding of enterprise security controls, secret management (Key Vault/KMS), and multi-environment deployment isolation
Proven track record in a client-facing technical lead role, with strong communication skills to drive enablement, workshops, and technical handovers
Skills
Azure Databricks
AWS Databricks
PySpark
MLflow
Delta Lake
Unity Catalog
Python
Databricks Asset Bundles (DABs)
Azure DevOps
GitHub Actions
Key Vault
KMS
About the role
We are seeking an experienced MLOps Lead Engineer to take full ownership of our enterprise Machine Learning operations on the Databricks Lakehouse platform. In this role, you will design, automate, and govern end-to-end ML production lifecycles—spanning continuous integration and deployment (CI/CD/CT), central governance, and real-time observability. You will act as the principal technical authority, bridging platform engineering with client-side operations by leading upskilling initiatives for onsite engineering teams.
Requirements
Required Qualifications & Experience
•
Experience: 8+ years in Data Engineering, Machine Learning Engineering, or DevOps, with 3+ years specifically leading Databricks MLOps/Data platform implementations.
•
Core Technical Stack: Advanced proficiency in Azure Databricks / AWS Databricks, PySpark, MLflow, Delta Lake, Unity Catalog, and Python.
•
Automation & DevOps: Strong experience building automated CI/CD/CT pipelines using Databricks Asset Bundles (DABs), Azure DevOps, or GitHub Actions.
•
Governance & Security: Deep understanding of enterprise security controls, secret management (Key Vault/KMS), and multi-environment deployment isolation.
•
Stakeholder Management: Proven track record in a client-facing technical lead role, with strong communication skills to drive enablement, workshops, and technical handovers.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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