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Data Platform Engineer

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Remote

Data Platform Engineer

Sterland Computing

Data Platform Engineer

Skills

PythonProduct ManagementPostgreSQLKafkaData AnalysisDatabase Administration

1 day ago

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Important information


Contract type:

Permanent

Location:

Sydney NSW, Australia

Work mode:

Remote

Published on:

22 October 2026

What they need


About DMSi

DMSi is a leading provider of ERP software solutions for the hardware, timber, and building materials industry across North America and Australia/New Zealand. For decades, we've been helping retailers, wholesalers, and trade merchants streamline their operations, manage inventory smarter, and grow their businesses with our Frameworks ERP platform.

We're a team that values innovation, customer obsession, and genuine partnerships with the businesses we serve. If you're passionate about B2B sales and want to make a real impact in the building materials industry, we'd love to hear from you.

The Opportunity

The Data Platform Engineer designs, builds, and evolves the data platform that powers analytics, reporting, and downstream integrations across DMSi products. This role owns the pipelines, schemas, and provisioning workflows that move data reliably from source systems into a scalable, multi-tenant analytics platform, and partners closely with database administration, infrastructure, and product teams to make that data available, accurate, and performant.
What You'll Do

  1. Design and build data pipelines that move data reliably from source systems into the analytics platform, using change data capture, event streaming, and related integration patterns.
  2. Design, implement, and maintain PostgreSQL schemas and data models that support scalable, multi-tenant analytics.
  3. Build and maintain the dashboard data layer that powers customer-facing analytics and reporting.
  4. Develop and maintain per-customer data provisioning workflows so new customers and data sources onboard onto the platform consistently.
  5. Apply infrastructure-as-code practices to provision, configure, and manage data platform environments in a repeatable and auditable way.
  6. Monitor data pipeline health, performance, and data quality, and troubleshoot and resolve latency, throughput, and accuracy issues.
  7. Partner with product management and engineering teams to translate reporting and analytics requirements into data platform capabilities.
  8. Collaborate with database administration and infrastructure teams to ensure the data platform integrates cleanly with the broader hosting environment and follows established security and access control standards.
  9. Document data platform architecture, data flows, and operational procedures to support ongoing maintenance, on-call response, and knowledge sharing across the team.
  10. Evaluate tools, platforms, and approaches that improve the reliability, scalability, and performance of the data platform, and recommend adoption where warranted.

What We're Looking For:

Strong hands-on experience with PostgreSQL, including schema design, query optimization, and data modeling for analytical workloads.
Experience with Kafka or a comparable event streaming or message platform, including change data capture pipeline design.
Experience with cloud infrastructure and infrastructure-as-code tooling.
Proficiency in at least one programming or scripting language, such as Python, for pipeline and automation development.
Familiarity with data modeling principles for multi-tenant, analytics-oriented systems.
Working knowledge of data security and access control practices appropriate to a multi-tenant analytics environment.
Strong problem-solving skills and the ability to work independently through ambiguous technical problems.
Clear written and verbal communication skills, including the ability to document technical designs for both technical and non-technical audiences.
Experience with monitoring and observability tooling is a plus.

Education and Experience:
Bachelor’s Degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
Three or more years of experience building and operating data pipelines, data platforms, or database-backed systems in production.

Work Environment and Physical Demands:
Normal office environment with use of computers and telephone systems; no unusual physical demands. 
Travel to customer locations as needed, including overnight stays, business air travel, and car rentals.
May require occasional off-hours availability to support on-call rotations or planned maintenance windows.

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