About The Role

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.