Pre-Sales Senior Data Solutions Architect for AI Platforms

World Wide Technology; Sydney; On-site; AUD 190,000 - 270,000; Full time

Benefits offered by this job

Health and wellbeing benefits

Profit sharing

Tuition reimbursement

Paid time off

Job summary

World Wide Technology is seeking a Technical Solutions Architect (Data Engineering) to drive data platform design and AI readiness. The role partners with account teams to translate complex data concepts into business value and to identify services opportunities across AI Studio, Foundry, and Factory offerings.

The candidate will lead data strategy, data engineering maturity, and governance discussions, leveraging Snowflake, Databricks, and modern lakehouse architectures across cloud platforms.

Qualifications

• 10+ years designing, building and optimizing scalable data platforms.
• Deep hands-on experience with Snowflake, Databricks, and modern Lakehouse.
• Strong SQL and Python skills for production quality code.

Responsibilities

• Lead pre‑sales engagements including workshops and architecture reviews.
• Translate technical concepts into business outcomes for executives.
• Advise on data strategy, data engineering maturity and AI‑ready data.
• Develop content such as whitepapers and enablement materials.
• Collaborate with partners like Databricks and Snowflake to validate approaches.
• Guide data platform migrations and advise on governance.

Skills

Snowflake

Databricks

SQL

Python

Data architecture

ETL/ELT

Cloud data platforms

Pre-sales

Stakeholder communication

Governance

Education

Bachelor’s degree in computer science, data engineering, or related field

Tools

Azure

AWS

Google Cloud

Job description

World Wide Technology is seeking a Technical Solutions Architect (Data Engineering) to drive data platform design and AI readiness. The role partners with account teams to translate complex data concepts into business value and to identify services opportunities across AI Studio, Foundry, and Factory offerings.

The candidate will lead data strategy, data engineering maturity, and governance discussions, leveraging Snowflake, Databricks, and modern lakehouse architectures across cloud platforms.