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Honeywell · 6 hours ago

Data Engineering Director

Atlanta, GA

Full-time

Onsite

Director/Executive

10+ years exp

Honeywell is a leading organization focused on solving complex challenges in automation and energy transition. The Data Engineering Director will shape and scale the Honeywell Forge Data Platform, driving AI and Autonomous solutions while leading a high-performing data engineering team.

AerospaceElectronicsInformation TechnologyInnovation ManagementManufacturingService Industry

Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Define and own the Honeywell connected data engineering strategy, reference architecture for AI-ready data, including cloud platform, data-as-a-service, and automation-first delivery model. Develop and communicate the enterprise data strategy and roadmap, ensuring alignment product requirements, and innovating for data as a service

Lead architectural decisions for Honeywell Forge Data Lake comprising IT and OT data, CDC, and integration with multiple source systems; handle reuse, performance, cost efficiency, and time-to-market

Architect, implement, and operate hybrid and cloud-native data platforms with heavy automation

Establish trusted domains focusing on security, governance, and reuse across business lines. Lead the design and delivery of reusable, trusted data as a service with clear SLAs, documentation, versioning, and APIs; enforce data contracts for product requirements

Enable secure, governed data sharing and monetization

Provide platform services and reusable capabilities for data science and AI: feature store, model-ready curated layers, governed sandboxes, MLOps integration, and model/data lineage

Embed data governance within pipelines: lineage capture, data classification, role-based and attribute-based access, fine-grained controls, and consent management

Implement data quality by design: thresholding, anomaly detection, reconciliation, and data SLAs enforced in CI/CD and runtime with automated quarantine/retry/escalation

Support build-vs-buy decisions, licensing, cloud spend, and vendor relationships. Scale teams and partners globally while building strong relationships with executives, technical teams, vendors, and business partners to understand needs, influence strategy, and promote best practices

Oversee platform implementation projects, balancing innovation, cost-effectiveness, and risk management

Scale, mentor, and inspire a diverse, high-performing data engineering and architecture team; develop adaptive hiring and resourcing strategies reflecting organizational growth and transformation

Ensure compliance with all risk, regulatory, and audit standards, and maintain rigorous internal controls

Qualification

Data architectureData engineeringCloud-native platformsAI/ML integrationData governanceData modelingBig data processingEvent-driven architecturePeople leadershipExecutive presenceStakeholder engagementTechnical communication

Required

Due to compliance with US export control laws and regulations, candidate must be a US Person which is defined as a US citizen, US permanent resident, or have protected status In the US under asylum or refugee status or have the ability to obtain an export authorization

10 or more years in data engineering and/or data and analytics, including 5 or more years leading large-scale data engineering and platform teams in complex environments

Deep expertise in data architecture and engineering: data modeling (OLTP/OLAP), big data and query engines, lakehouse, data warehousing, MDM, data integration, CDC, and large-scale batch/stream processing

Experience delivering data products at scale with embedded governance, metadata/lineage, and continuous DQ; strong background in data contracts and data observability

Time series data streaming expertise, event-driven architectures, and change data capture patterns. Proven success designing and operating enterprise cloud-native data platforms on at least one hyperscaler

Practical experience enabling AI/ML: feature stores, model-ready datasets, MLOps integration, and privacy-preserving patterns; comfortable partnering with data scientists and ML engineers

Executive presence with the ability to translate complex architectures into business value, present to senior leadership/board-level stakeholders, and lead through influence

5 or more years of people leadership, including hiring, performance management, coaching, and org design

Bachelor's degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics

Preferred

Bachelor's or Master's degree in Computer Science, Engineering, or related discipline (STEM preferred)

Experience in industrial plants, buildings operations, knowledge of domains such operational efficiency, energy savings, predictive maintenance and operational optimization

Familiarity with data monetization, secure data sharing, and analytics in hybrid platforms