Forward Deployed Data Engineer

Insulet Corporation

. Collaborate with business, product, analytics, and AI teams to understand decisions, workflows, constraints, and value opportunities .

Posted 10/27/2026full-timeUnited StatesSeniorLead💰 $143,700 - $215,550 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying cloud-scale data products, leveraging modern engineering practices and AI technologies. Proven ability to lead cross-functional teams in delivering complex data solutions while ensuring compliance with security and regulatory standards.

Highest-signal resume keywords

Data EngineeringCloud-Scale Data ProductsGenerative AIDistributed Data ProcessingLeadership in Complex Enterprise Delivery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingAPIsEvent StreamingDevOpsDataOpsInfrastructure as CodeObservabilityData QualityData ArchitectureAI-Assisted Software Development

Soft Skills

CollaborationCoachingCommunicationProblem-SolvingLeadership

Tools & Technologies

AWSAzureDatabricksSnowflakeKafkaDbtSparkKubernetesTerraformGitHub

Industry Keywords

HealthcareMedical DevicesLife SciencesDigital HealthRegulated IndustriesPrivacySecurityResponsible AIAuditabilityEnterprise Governance

Tech Stack

Tools & technologies

AWSAzureCloudERPKafkaKubernetesSnowflakeSparkTerraform

About the role

Key responsibilities & impact

Collaborate with business, product, analytics, and AI teams to understand decisions, workflows, constraints, and value opportunities
Translate ambiguous business challenges into data product charters, architecture hypotheses, experiments, MVPs, and scalable delivery plans
Build vertical slices connecting source data to trusted decisions, then harden prototypes into secure, supportable, reusable enterprise products
Partner with senior business and technology leaders to define outcomes, adoption measures, value cases, roadmaps, and priorities
Bridge data owners, model builders, application engineers, platform teams, Security, Privacy, Quality, and Compliance
Design and deliver AI-ready data foundations for predictive models, generative AI, RAG, knowledge systems, copilots, and agents
Use AI coding copilots and engineering agents across requirements discovery, profiling, code generation, testing, documentation, lineage, migration, incident triage, and optimization
Create governed agentic workflows with human review and approval controls
Engineer context layers combining structured data, documents, metadata, semantic models, vector representations, and business rules
Lead data products through discovery, architecture, production deployment, adoption, observability, and continuous improvement
Architect composable data products with domain ownership, interfaces, reusable services, data contracts, semantic standards, and lifecycle accountability
Design batch, streaming, event-driven, API-based, and change-data-capture patterns
Build metadata-driven pipelines, infrastructure as code, automated testing, CI/CD, environment promotion, and policy-as-code controls
Engineer data quality, lineage, security, privacy, access, retention, auditability, and regulatory requirements into products
Implement end-to-end observability for data and service performance
Apply cloud and AI FinOps practices to optimize resources against business value
Lead, coach, and develop Data Engineers and cross-functional delivery professionals
Create reference architectures, starter kits, reusable components, engineering playbooks, and paved-road patterns
Lead design reviews, code reviews, technical spikes, and post-implementation learning sessions
Build communities of practice and inform enterprise platform, standards, workforce, operating model, and investment decisions

Requirements

What you’ll need

Bachelor’s or Master’s degree in computer science, engineering, data science, information systems, or a related technical field
10+ years of experience in data engineering, software engineering, platform engineering, or data architecture, including leadership of complex enterprise delivery
Ability to design, code, test, deploy, and operate cloud-scale data products using modern engineering practices
Strong experience with distributed data processing, data modeling, orchestration, APIs, event streaming, DevOps, DataOps, observability, and infrastructure as code
Practical understanding of generative AI, large language models, retrieval-augmented generation, vector search, AI agents, model integration, and AI-assisted software development
Ability to lead data products from discovery through MVP, production deployment, adoption, and continuous improvement
Hybrid working arrangement requiring on-site work from an Insulet office
Preferred: Experience in healthcare, medical devices, life sciences, diabetes care, digital health, or regulated industries
Preferred: Experience with AWS, Azure, Databricks, Snowflake, Kafka, dbt, Spark, Kubernetes, Terraform, GitHub, or similar enterprise technology ecosystems
Preferred: Experience establishing data product operating models, data contracts, semantic layers, real-time architectures, or self-service engineering platforms
Preferred: Experience modernizing legacy data estates and integrating ERP, CRM, manufacturing, supply chain, quality, commercial, clinical, or connected-device data
Preferred: Familiarity with privacy, security, validation, responsible AI, auditability, and enterprise governance requirements for data and AI solutions

Benefits

Comp & perks

Medical, dental, and vision insurance
401(k) with company match
Paid time off (PTO)
Additional employee wellness programs
Incentive compensation eligibility