Lead DataOps / MLOps

🕒 Setembro 22

🏈 Alabama, Nebraska – Remoto

🏈 Alabama – Remote 🌾 Nebraska – Remote

💵 $124.500 - $170.000 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Protective Life

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1908

💸 Finanças

🛡️ Seguros

Finance • Insurance

A Protective Life é uma empresa de serviços financeiros especializada em oferecer seguros de vida e anuidades acessíveis. A empresa oferece uma variedade de produtos de seguro, como apólices de seguro de vida temporário, vida inteira e vida universal, bem como anuidades fixas, imediatas, indexadas e variáveis. A Protective Life auxilia indivíduos no planejamento de seu futuro, incluindo aposentadoria, planejamento patrimonial e proteção financeira para famílias. A empresa enfatiza seu compromisso com a sustentabilidade, envolvimento comunitário e ajuda aos clientes a alcançarem proteção e segurança ao longo de diversas fases da vida. A Protective Life é conhecida por sua forte base financeira e está licenciada para operar em todos os estados, exceto Nova York.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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