R&D principal iot data pipeline architect

Location: U.S.A based - Remote

Segment: InSite

Direct Report To: Senior R&D Director

Duracell is seeking a Principal IoT Data Platform Architect to own the architecture, implementation framework, security, governance, and evolution of the Procell InSite data platform. This role spans IoT devices, Azure, Databricks, analytics, AI/ML, APIs, and customer-facing applications.

This hands-on technical authority will set standards, implement and test critical platform elements, establish secure reusable frameworks, and drive scalability, reliability, and product innovation. The role is a senior individual contributor operating through technical leadership and direct contribution.

Data Platform Leadership

• Own the platform roadmap, target architecture, transition plans, technical debt priorities, and architecture decisions.
• Lead architecture and implementation across device-to-cloud ingestion, storage, processing, analytics, APIs, and applications.
• Establish reference architectures, engineering standards, reusable frameworks, decision records, and exception controls.
• Define system boundaries and integration contracts across Firmware, Cloud, Data, Software, Analytics, Security, Product, and IT.
• Translate product needs into measurable requirements for latency, scale, availability, recovery, quality, security, and cost.

Data Engineering & Architecture

• Design and implement batch, streaming, event-driven, and API-based pipelines connecting devices, cloud services, analytics, and applications.
• Own the telemetry lifecycle from device identity and ingestion through validation, enrichment, storage, serving, retention, and deletion.
• Define event schemas, data models and contracts, schema evolution, replay, idempotency, deduplication, and ordering controls.
• Implement lakehouse and streaming patterns with governed raw, validated, curated, and product-ready data layers.
• Create scalable storage, processing, and serving patterns for telemetry, alerts, APIs, analytics, AI/ML, and low-code applications.
• Establish data quality, lineage, observability, ownership, issue routing, and measurable service levels.
• Build production-ready reference implementations and perform integration, contract, performance, resilience, security, and regression testing.
• Lead capacity planning, workload isolation, scale testing, backfill, correction, replay, and migration strategies.

Governance & Security

• Own Procell InSite governance for metadata, stewardship, classification, retention, lineage, auditability, and trusted datasets.
• Define Unity Catalog architecture and integration with the enterprise governance ecosystem.
• Implement least-privilege access, managed identities, secrets, encryption, key management, private connectivity, and security monitoring.
• Own secure platform boundaries across Azure, Databricks, storage, networks, environments, APIs, and customer tenants.
• Ensure tenant isolation and alignment with enterprise, contractual, privacy, cybersecurity, residency, retention, and audit requirements.
• Perform threat modeling and security reviews for ingestion, data sharing, APIs, AI, and external integrations.

Cloud & Platform Strategy

• Define and implement Azure and Databricks architecture and guardrails for ingestion, storage, processing, orchestration, serving, governance, and monitoring.
• Own platform topology across subscriptions, resource groups, environments, regions, networks, identities, storage, and workspaces.
• Implement infrastructure as code, source control, automated testing, CI/CD, environment promotion, deployment validation, and rollback.
• Establish service objectives and observability for ingestion, latency, freshness, availability, performance, and recovery.
• Define disaster recovery, backup, restore, RTO/RPO, regional recovery, dependency-failure, and recovery-testing strategies.
• Drive capacity forecasting, cost attribution, budget controls, unit-cost measurement, platform lifecycle, and build-versus-buy decisions.

Technical Leadership

• Serve as the technical authority, approve target architectures and standards, and lead design and exception reviews.
• Convert approved designs into working frameworks, reference implementations, test strategies, and production-ready patterns.
• Remain hands-on in critical design, coding, configuration, prototyping, troubleshooting, performance testing, and security validation.
• Partner across engineering, product, cybersecurity, QA, operations, IT, and strategic vendors to deliver integrated solutions.
• Mentor engineers and architects and communicate technical tradeoffs, risks, and investment recommendations to leadership.

Must-Have

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
• 10+ years in cloud, software, data engineering, or platform architecture, including 5+ years leading complex production data-platform architecture.
• Demonstrated hands-on ownership of large-scale production cloud data platforms and secure multi-tenant architectures.
• Production experience with IoT telemetry, event-driven systems, high-volume streaming, and distributed-system failure modes.
• Deep experience with Azure and Databricks, including Spark, Delta Lake, lakehouse design, performance optimization, and Unity Catalog.
• Experience with IoT Hub, Event Hubs, Kafka, Structured Streaming, or comparable event and streaming technologies.
• Strong SQL and proficiency in Python, Scala, Java, C#, or a comparable platform-development language.
• Experience with data modeling, APIs, integration contracts, infrastructure as code, CI/CD, automated testing, and observability.
• Experience implementing security, governance, lineage, access controls, tenant isolation, auditability, disaster recovery, and cloud cost controls.
• Ability to turn ambiguous product requirements into secure, testable architectures, working implementations, and executable roadmaps.
• Ability to defend architecture decisions with engineering, cybersecurity, enterprise architecture, product, vendors, and executives.

Nice-to-Have

• Experience with connected-device fleets, device registries or twins, real-time alerting, and condition-monitoring platforms.
• Experience with customer-facing Data-as-a-Service, SaaS, governed data sharing, Power BI, low-code, or generative AI platforms.
• Experience leading platform modernization or migration while maintaining production availability.
• Azure or Databricks certifications; master's degree in a technical discipline.