Platform Engineer

• Be a part of transformational change where integrity matters, success inspires and great teams collaborate and innovate.
• Contribute toward the success of our technology initiative developing a modern analytics platform for the business.
• Deep understanding of at least one major cloud provider (Azure or AWS) regarding networking (VNet/VPC, PrivateLink), storage (ADLS Gen2, S3), and IAM.
• Advanced Proficiency in at least one programming language.
• Extensive experience with Terraform and the Databricks Terraform Provider to manage workspace resources, clusters, and permissions.
• Extensive Experience building and using automation pipelines using GitLab or similar for CICD and Databricks Asset Bundles (DABs).
• Responsible for designing, developing, testing, operating and maintaining products.
• Takes full stack ownership by consistently writing production-ready and testable code.
• Makes sound design/coding decisions keeping customer experience in the forefront.

Senior Data Analytics Platform Engineer, Databricks

• Provision and manage cloud infrastructure across compute, networking, storage, and managed databases
• Maintain consistency across development, staging, and production environments
• Plan and execute workload migrations across cloud providers with minimal disruption
• Identify and implement infrastructure cost optimization opportunities
• Build and maintain CI/CD pipelines across a multi-repository environment
• Implement deployment strategies such as blue/green, canary, and rolling deployments
• Develop automation tooling and scripts to reduce manual effort and improve delivery speed
• Write and maintain Terraform infrastructure across multi-account, multi-environment systems
• Establish IaC standards, module reuse patterns, and state management practices
• Drive infrastructure changes through version-controlled, peer-reviewed workflows
• Participate in on-call rotation and lead incident response efforts
• Maintain observability through dashboards, alerting, logging, and SLO tracking
• Conduct post-incident reviews and implement long-term remediations
• Manage secrets, certificates, and access controls using least-privilege principles
• Apply security best practices across infrastructure, containers, and CI/CD pipelines
• Support audit and compliance initiatives through documentation and access reviews
• Partner with engineering teams on infrastructure guidance and service design
• Create architecture documentation, runbooks, and operational guides
• Help build self-service platform capabilities for engineering teams

Senior Platform Engineer

• As a Senior Data Platform Engineer, you’ll be a hands-on engineer on a small, high-ownership data team.
• You’ll work across the full data platform - relational, warehouse, and lakehouse systems - building and operating the pipelines that power compliance, analytics, and reporting workloads.
• Design and build pipelines that move data across systems - supporting data lake ingestion, compliance workloads, and cross-domain data flows.
• Own pipeline operations end to end: monitoring, incident resolution, data quality, and documentation that lets any team member respond independently.
• Identify technical debt and reliability risks and raise them with clear context and proposed next steps.
• Design and maintain schemas across relational, warehouse, and lakehouse layers, working with application engineers and product to get data models right.
• Build out the platform’s service layer, infrastructure-as-code, and data quality frameworks - this role spans design and implementation.
• Keep platform documentation at a level where any team member can understand what exists, how it works, and where the risks are.
• Over time, contribute to the analytics engineering layer, including modeling practices and semantic layer development.
• Contribute to evaluations of the current platform against emerging architectures and tooling, helping produce trade-off analyses and recommendations.
• Bring what you see day to day in the systems you operate into the team’s improvement roadmap and technical direction.
• Track and report on platform health metrics: pipeline uptime, failure rates, data freshness, and cost trends.
• Mentor peers and junior engineers through code review, pairing, and technical guidance.

Senior Data Platform Engineer

• Contribute toward the success of developing a modern analytics platform for the business.
• Deep understanding of cloud provider features (Azure or AWS) regarding networking, storage, and IAM.
• Building and using automation pipelines for CICD and Databricks Asset Bundles.
• Managing workspaces, compute resources, and other related activities.
• Designing, developing, testing, operating, and maintaining products.
• Writing production-ready and testable code.
• Reviewing tasks and ensuring they are appropriately prioritized and sized for incremental delivery.

Senior Data Analytics Platform Engineer – Databricks

• Define and maintain golden paths for service creation, including service templates, starter kits, and scaffolding tools that let teams go from zero to production-ready with minimal friction
• Own developer onboarding workflows and maintain high-quality platform documentation
• Establish and evolve CI/CD pipeline standards across the organization
• Design release automation patterns, including rollout safety mechanisms such as canary deployments, progressive delivery, and automated rollbacks
• Build and maintain internal platform portals, reusable infrastructure modules, and paved-road workflows
• Enable product engineering teams to provision resources, configure environments, and ship features independently without reliance on other teams
• Champion platform adoption through clear documentation, enablement sessions, and a consultative approach
• Measure developer satisfaction and platform adoption metrics to continuously improve the experience
• Partner with product engineering, infrastructure, and operations teams to ensure platform tooling meets cross-platform needs
• Translate engineering pain points into scalable platform capabilities• Embed security and compliance requirements such as SOC2 and PCI-DSS into platform tooling and CI/CD pipelines

• Own the operational lifecycle of AI agents deployed across PEMCO: deployment, monitoring, scaling, incident response, and retirement.
• Build and maintain observability for the AI layer, including cost tracking, latency, error rates, model performance, token usage, and production monitoring for agent workers.
• Manage agent orchestration infrastructure, including configuration, versioning, connection management, and tool registration. Current stack includes MCP-based orchestration and Azure OpenAI services.
• Establish runbooks and incident response procedures for AI agent failures. When an agent supporting a business workflow goes down, this role owns the recovery.
• Implement prompt governance controls and role-based model access per Information Security standards: PII exposure monitoring, prompt injection detection, and access enforcement. Contribute requirements and technical capabilities to InfoSec for AI-specific policy development.
• Build the enterprise agent marketplace: deploy and manage AI agents within an enterprise UI framework, ensuring discoverability, versioning, and access controls.
• Evaluate new model releases, track capability evolution, and make recommendations on model selection. Maintain a knowledge management layer for AI operations including decision logs, model inventories, and governance documentation.
• Contribute directly to AI governance and the AI Governance Working Group. Operationalize security, governance, and compliance standards defined by Information Security and Data & AI leadership across all AI deployments.
• Optimize AI infrastructure costs through model selection, caching strategies, batching, and token budget management.
• Partner with the Data & AI team on production readiness for models and agents. Data & AI owns model development, training, and AI governance policy. This role owns the operational deployment, monitoring, fallback behavior, graceful degradation, and knowledge layer integration.
• As the function matures, define team structure, secure headcount, and build a team.
• Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics, and business conduct.
• Authentically support the PEMCO Brand and constantly are on the lookout for top talent to join us to achieve our Mission to Worry Less and Live More.
• Other duties as assigned.

Principal AI Platform Engineer

• Design and implement scalable infrastructure solutions across AWS, on-prem, and hybrid environments
• Build and maintain reusable Infrastructure as Code (IaC) modules and platform components
• Develop and enforce secure-by-design solutions aligned to CMMC Level 2 and enterprise security requirements
• Partner with Security Architecture and GRC to translate security and compliance requirements into implementable controls
• Lead the implementation of network segmentation, identity integration, logging, and monitoring solutions
• Drive adoption of automation-first practices, including CI/CD pipelines and Policy as Code (PaC)
• Solve complex platform and infrastructure challenges through hands-on engineering and rapid iteration
• Contribute to and refine platform standards, patterns, and reference implementations through working code
• Support and mentor engineering teams on best practices for infrastructure, automation, and platform design
• Evaluate and integrate new technologies (including AI-enabled platforms) with a focus on practical implementation and risk alignment

Principal Platform Engineer

• Design, develop, and maintain Infrastructure as Code (IaC) using Terraform or similar tools
• Design and operate CI/CD pipelines supporting infrastructure and platform services
• Implement and maintain Policy as Code (PaC) to enforce security and compliance standards
• Design and support multi-account cloud environments and landing zones
• Contribute to the development of reusable platform modules, standards, and reference architectures
• Automate provisioning, configuration, and lifecycle management of infrastructure
• Collaborate with Security and Architecture teams to enforce CMMC-aligned controls
• Improve platform reliability through automation, standardization, and self-service capabilities
• Support integration of identity, logging, and monitoring services across environments

See all jobs on JobTailor

Senior Data Analytics Platform Engineer, Databricks

Senior Platform Engineer

Senior Data Platform Engineer

Senior Data Analytics Platform Engineer – Databricks

Senior Platform Engineer

Principal AI Platform Engineer

Principal Platform Engineer

Platform Engineer