Data Platform & AI Solution Architect
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Monthly Salary:
Posted on:
13 hours ago
Vacancies:
1 Vacancy
Job Summary
Career Area:
EngineeringJob Description:
Your Work Shapes the World at Caterpillar Inc.
When you join Caterpillar yourejoining a global team who cares not just about the work we do but also about each other. We are the makers problem solvers and future world builders who are creating stronger more sustainable communities. We dontjust talk about progress and innovation here we make it happen with our customers where we work and live. Together we are building a better world so we can all enjoy living in it.
Own the end-to-end architecture and operating model for the data platform powering analytics and AI. This includes data repositories (lakehouse/warehouse) enterprise reporting strategy AI-ready data capabilities engineering platform design and the integration & operationalization of data science models (ML & GenAI). Youll translate strategic business outcomes into scalable secure and cost efficient data and AI solutions enabling self service trust and rapid delivery.
Key Responsibilities
Data Repository Architecture & Governance
Define the target-state architecture (lakehouse/warehouse zones: raw/bronze curated/silver serving/gold) and data product strategy.
Establish data modeling standards (dimensional/star data vault wide tables Delta/Iceberg/Hudi) for batch and streaming.
Implement metadata cataloging lineage and data contracts; standardize schema evolution and versioning.
Drive security & compliance (RBAC/ABAC encryption masking PII handling consent/retention) and cost/performance optimization.
Set and enforce SLA/SLOs for availability freshness and reliability with full data observability (logs metrics traces).
Enterprise Reporting & BI Strategy
Define the semantic layer and metric store to standardize KPI definitions across BI tools (Power BI/Tableau/Looker).
Build governed datasets and self service enablement models with certified dashboards and release/version management.
Create a data storytelling & usability framework (accessibility performance load patterns caching).
Establish data product ownership lifecycle management SLAs change control and audit for BI assets.
Data Needs for AI
Architect AI-ready data pipelines: labeling feature stores embeddings vector search training/validation/inference data management.
Data Engineering Platform Architecture
Design the data engineering platform: ingestion (batch/streaming) transformation orchestration testing observability deployment.
Provide platform blueprints and reusable scaffolding/SDKs to accelerate pipeline development.
Establish DevEx standards: CI/CD for data pipelines environment strategy (dev/test/prod) infra as code (Terraform etc).
Implement monitoring & alerting (freshness volume anomalies schema drift SLA breaches) and DQ testing (Great Expectations/dbt tests).
Own capacity planning cost governance partitioning/file layout and performance tuning.
Integrating Data Science Models (Operationalization)
Define model serving architectures (batch scoring online inference streaming) with A/B testing and canary deployments.
Build feature lifecycle management: creation reuse drift detection backfills and documentation.
Integrate models with data contracts lineage and model observability (data drift performance fairness latency).
Enable low-latency APIs and event-driven inference; ensure scale reliability and rollback capabilities.
Qualifications
Extensive years of experience in data engineering/architecture; years of experience with platform/solution architecture leading enterprise initiatives.
Deep expertise in distributed systems (Spark/Flink) streaming (Kafka/Kinesis) lakehouse (Delta/Iceberg/Hudi) and warehouses (Snowflake/BigQuery/Redshift/Synapse).
Strong hands on with Python/Scala/SQL orchestration (Airflow/Dagster/ADF) dbt and CI/CD (GitHub Actions/Azure DevOps/Jenkins).
Experience with semantic/metric layers and BI tools (Power BI/Tableau/Looker).
Knowledge of ML Ops & LLM Ops ( Preferable)
Security & compliance mindset: IAM/RBAC encryption data masking privacy laws (GDPR/DPDP) Responsible AI practices.
Proven stakeholder leadership; excellent communication and product mindset.
Core Competencies
End to End Architecture: Designs across data analytics and AI workflows and operating models.
Platform Product Thinking: Treats the platform and data assets as products (roadmaps SLAs adoption).
Reliability & Performance: Builds resilient cost efficient systems with clear metrics.
Enablement & Influence: Drives cross functional alignment and self service adoption.
Risk & Compliance: Balances innovation with governance security and regulatory needs.
Benefits:
Competitive remuneration package including a great bonus structure and share options.
Intentional career development with exposure to global teams and markets.
A strong commitment to safety and your wellbeing
An inclusive workplace culture focused on quality customer service and the environment
A commitment to diversity and inclusion equal opportunity and equal outcome
The opportunity to do truly meaningful work in a supportive constructive culture that encourages you to make the most of your talents.
Caterpillar of Australia is not currently hiring foreign national applicants that require or will require sponsorship.
Relocation is available for this position.Posting Dates:
December 3 2025 - December 20 2025Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply
Not ready to apply Join our Talent Community.
Key Skills
- Business Process
- VMware
- Cloud
- HTML5
- Windows
- Project managements
- AWS
- Infrastructure
- Web Services
- JQuery
- Java
- Computer Engineering
- Solutions design
- Technical Solutions
- Analytics
About Company
Caterpillar is the world’s leading manufacturer of construction and mining equipment, diesel and natural gas engines, industrial turbines and diesel-electric locomotives.
