Lead Data Engineer responsible for architecting and owning data foundations for Honeywell's Industrial AI & Data Platforms, driving technical leadership, and building AI-ready data products.
Compensation
In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package.
Responsibilities
Architect end-to-end data pipelines processing terabytes of IoT telemetry on Azure Databricks
Design and optimize real-time ingestion pipelines from Azure Event Hub and Apache Kafka
Design, develop, and maintain data infrastructure and analytical solutions that transform complex, multi-source datasets into reliable, actionable information.
Responsibilities
Design, develop, and maintain scalable data pipeline architectures to support enterprise data and analytics initiatives.
Implement cloud-based data solutions using AWS services, including S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.
Develop and maintain data orchestration workflows using Apache Airflow, AWS Step Functions, or comparable technologies.
Integrate, extract, transform, and load large, complex datasets from multiple sources using SQL and big data technologies.
Build and optimize analytical data environments that support statistical analysis, predictive modeling, machine learning, and research initiatives.
Lead Data & AI Solutions Architect – Government & Infrastructure sector, focusing on pre‑sales solutioning and delivery of cloud data and AI solutions
Responsibilities
Serve as a key Lead Data & AI Solutions Architect – Government & Infrastructure sector, focusing on pre‑sales solutioning and the successful delivery of cloud data and AI solutions
Collaborate closely with sales and account teams to thoroughly understand client requirements and tailor solutions accordingly
Lead the Cloud Data Architecture and Delivery teams, ensuring they possess the necessary skills and capabilities to deliver innovative, high‑quality solutions that meet sector‑specific needs
Engage in client meetings and workshops to gather insights, refine solution offerings, and present compelling business cases that demonstrate the return on investment (ROI) of our solutions
Develop and present tailored Go‑To‑Market strategies and solutions that align with best practices in the Government and Infrastructure sector, particularly in the context of AI and data analytics
Freelance AWS Data Platform Engineer responsible for building and maintaining containerized data platforms, shaping infrastructure, and ensuring scalable, secure solutions.
Locations (3)
Mechelen, Flanders, Belgium
Leuven, Flanders, Belgium
Gent, Belgium
Responsibilities
Build, manage, and continuously improve containerized data platforms with Kubernetes and AWS
Shape infrastructure and ensure industrialization for future-proof scalability
Partner with Data Architect to guide technical direction
Balance cost, performance, and maintainability in design
Implement production-ready solutions including deployment automation, monitoring, and alerting
Design and lead end‑to‑end Snowflake solutions, provide technical leadership, and serve as a trusted advisor to customers.
Compensation
Pay range: $128,000 - $193,200 depending on experience and skill set
Annual bonus target of 10% subject to terms and conditions of plan
Responsibilities
Manage team delivery against the Statement of Work
Perform hands‑on development in Snowflake, SQL, dbt, python
Design and lead implementation of end‑to‑end Snowflake architectures
Ensure project teams follow approved architecture, security, privacy, governance, source‑control, testing, deployment, and documentation standards
Review solution components and deliverables for technical accuracy, data quality, maintainability, performance, and alignment with customer requirements
Principal data architects play a key part in developing modern data architecture approaches to meet business objectives and provide end-to-end data solutions. They lead design, architecture of initiatives, and mentor delivery teams.
Responsibilities
Lead complex data programs, navigating architectural concerns and enabling delivery teams.
Provide client-facing technical leadership and guidance on data engineering, machine learning, and Agentic AI.
Interact with client counterparts from enterprise architecture groups to lead delivery and sign-off of architectural decisions.
Communicate trade-offs of different technology choices to stakeholders.
Map business outcomes with specific concrete business KPIs aligned with OKRs and KRAs.
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