Lead DataOps / MLOps

Ladders; United States; Remote; USD 125,000 - 170,000; Full time

Benefits offered by this job

Health, dental, vision insurance

Mental health support

Paid time off + parental leave + flex

401(k) with company match

Job summary

Ladders is seeking a Lead DataOps / MLOps to join a client leading in Finance & Insurance. The role shapes the operating model for data and ML pipelines, focusing on reliability, standardization, and automation at scale.

Remote work is offered with a compensation range of $124,500–$170,000 annually. You will partner with data engineering and ML teams to strengthen deployment practices, governance, and cost efficiency across Azure-based platforms.

Qualifications

• 8+ years in data, ML, or platform engineering.
• Demonstrated technical leadership and mentoring of engineers.
• Strong CI/CD expertise using Azure DevOps for data pipelines and ML models.
• Hands-on orchestration with Dagster and modern data stacks.
• MLOps experience with MLflow for model management and deployment.
• Proficient in infrastructure-as-code and Azure administration.
• Strong Python and SQL for automation.

Responsibilities

• Own the DataOps/MLOps platform and operating model for data and ML pipelines.
• Lead CI/CD standards and pipelines in Azure DevOps for deployment automation.
• Standardize orchestration processes using Dagster for pipeline management.
• Operationalize ingestion and transformation stacks including dlt and dbt.
• Establish foundations for MLOps with the ML engineering team using MLflow.
• Administer and govern the Databricks Lakehouse environment on Azure.
• Drive cost visibility and optimization across computing resources.

Skills

CI/CD with Azure DevOps

Dagster orchestration

MLflow for ML ops

Python

SQL

Azure cloud

Platform engineering

Tools

Azure DevOps

Dagster

MLflow

Databricks

dbt

Delta Live Tables

Job description

For our client, we are seeking a Lead DataOps / MLOps to join the team of a leader in the Finance & Insurance space.

This role will shape the operating model for data and machine learning pipelines, with a focus on reliability, standardization, and automation at scale. You will partner closely with data engineering and ML teams to strengthen deployment practices, improve orchestration, and support production-ready workflows. The position also plays a key role in governing the cloud-based data platform and driving better visibility into infrastructure usage and cost efficiency.

Location: Remote

Compensation: $124,500 – $170,000 annually

Responsibilities

• Own the DataOps/MLOps platform and operating model for data and ML pipelines.
• Lead CI/CD standards and pipelines in Azure DevOps for deployment automation.
• Standardize orchestration processes using Dagster for pipeline management.
• Operationalize ingestion and transformation stacks including dlt and dbt.
• Establish foundations for MLOps with the ML engineering team using MLflow.
• Administer and govern the Databricks Lakehouse environment on Azure.
• Drive cost visibility and optimization across computing resources.

Qualifications

• 8+ years in data, ML, or platform engineering, or in SRE/DevOps with production experience.
• Demonstrated technical leadership in setting standards and mentoring engineers.
• Strong CI/CD expertise using Azure DevOps for data pipelines and ML models.
• Hands-on experience with orchestration tools like Dagster and modern data stacks.
• MLOps experience with MLflow for model management and deployment.
• Proficient in infrastructure-as-code and Azure platform administration.
• Strong Python and SQL skills for automation.

Benefits

• Comprehensive health, dental, and vision insurance.
• Mental health support through employee assistance programs.
• Variety of paid time off benefits including parental leave and cultural days.
• 401(k) plan with company matching and pension contributions.
• Wellbeing rewards program with cash incentives.

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.