Lead DataOps / MLOps

🔥 13 minutes ago

🏈 Alabama, Nebraska – Remote

🏈 Alabama – Remote 🌾 Nebraska – Remote

💵 $124.5k - $170k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

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Protective Life

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1908

💸 Finance

🛡️ Insurance

Finance • Insurance

Protective Life is a financial services company specializing in providing affordable life insurance and annuities. The company offers a variety of insurance products such as term life, whole life, and universal life policies, as well as fixed, immediate, indexed, and variable annuities. Protective Life assists individuals in planning for their future, including retirement, estate planning, and financial protection for families. The company emphasizes its commitment to sustainability, community involvement, and helping customers achieve protection and security throughout various life stages. Protective Life is known for its strong financial foundation and is licensed to operate in all states except New York.

📋 Description

• Own the DataOps/MLOps platform and operating model, including paved paths, automation, and tooling for data and ML engineers • Lead CI/CD standards and Azure DevOps pipelines for data pipelines and ML models • Build, test, release, promote, and audit deployments across environments • Standardize orchestration on Dagster, including reusable assets, scheduling, backfills, dependency management, and run observability • Operationalize dlt ingestion and dbt transformation with automated testing and CI checks • Build MLOps foundations with MLflow model registry, Databricks Model Serving, deployment automation, monitoring, drift detection, and retraining triggers • Establish data and model observability for freshness, quality, lineage, latency, drift, and cost, with alerting and SLAs/SLOs • Administer and govern the Databricks Lakehouse on Azure, including workspace configuration, Unity Catalog, access controls, and policy automation • Manage infrastructure as code and reproducible development, test, and production environments • Own reliability and incident practices, including on-call, runbooks, root-cause analysis, and continuous improvement • Drive FinOps cost visibility and optimization across compute, storage, and model serving • Automate governance and compliance controls, including audit logging, inventories, approval workflows, and evidence collection • Provide technical leadership and mentor engineers on operational excellence and platform standards

🎯 Requirements

• 8+ years in data, ML, or platform engineering, or in SRE/DevOps, including several years operating production data and/or ML systems • Demonstrated technical leadership, including setting standards, building paved paths and automation, and mentoring engineers • Strong CI/CD expertise with Azure DevOps (ADO), including build/release pipelines, environment promotion, and automated testing • Git-based workflow experience • Hands-on experience with orchestration such as Dagster or equivalent • Experience with dlt (dltHub) ingestion and dbt modeling • Experience with Databricks Lakehouse and Delta Lake • MLOps experience with MLflow model registry, model deployment/serving, monitoring, drift detection, and retraining automation • Infrastructure-as-code and Microsoft Azure cloud platform administration, including compute, storage, identity, and networking basics • Terraform or equivalent experience • Strong Python and SQL skills • Experience with observability/monitoring tooling and SRE practices, including SLAs/SLOs, alerting, and incident management • Rigor in security, access control, and secure, compliant handling of sensitive data • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience • Preferred: financial services or insurance platform experience; familiarity with model risk and regulatory audit expectations • Preferred: Databricks administration, Unity Catalog, cluster policies, Mosaic AI, and Azure Machine Learning • Preferred: Docker, Kubernetes, Azure AKS, or Container Apps • Preferred: data-quality/observability tooling such as Great Expectations or Monte Carlo • Preferred: responsible-AI and model-governance automation • Preferred: relevant Databricks or Microsoft Azure certification

🏖️ Benefits

• Comprehensive health, dental, and vision insurance • Mental health benefits • Employee assistance program • Paid time off • Paid parental leave • Short-term disability • Cultural observance day • Contributions to healthcare accounts • Pension plan • 401(k) plan with Company matching • ProHealth Rewards wellness platform with cash rewards • Annual incentive based on individual and Company performance • Remote work arrangement