Principal Technical Business Analyst - Data Products & Platforms
About the job
- Have a background as a data-focused technical business analyst, engagement analyst, consultant, or as an engineer or analyst moving into an analyst role.
- Understand how data moves, is structured and sourced, and what it means in business terms.
- Be fluent in SQL and independently explore, profile, and validate data.
- Read and reason about data models and source-to-target mappings; know a modern cloud data stack and ETL or ELT.
- Demonstrate strong requirements craft, including elicitation, workshops, acceptance criteria, backlog management, and RAID.
- Be able to elicit, analyze, and prioritize requirements; advocate for customers and serve as a stakeholder proxy; apply critical thinking, problem solving, and logical reasoning; translate business intent into technical delivery; and facilitate workshops, define acceptance criteria, validate, and support UAT.
- Have strong, structured written skills for status reports, proposals, and specifications; communicate clearly with executives and independently produce high-quality materials.
- Act as the customer's proxy within delivery on data platform and data product engagements.
- Understand client problems deeply, form and defend a clear point of view, shape solutions alongside the tech lead, and produce requirements and documentation that keep engagements moving.
- When appropriate, apply a data product perspective focused on outcomes, prioritisation, and value across data platform, data product, and governance initiatives.
- Explore, profile, and validate data independently using SQL.
- Exposure to Databricks, Snowflake, BigQuery, dbt, Azure, AWS, or GCP.
- Exposure to data modelling, source-to-target mapping, data pipelines, ETL or ELT, Jira, and Confluence.
About the company
Simple Machines is an Australian consultancy that fuses data architecture, data engineering, data science, and software development to create large-scale, distributed data platforms and machine learning applications. They design end-to-end data systems that handle streaming and batch data at scale, helping organizations operationalize analytics and AI in real-world settings. They differentiate themselves through enterprise-grade streaming platforms and formal partnerships with Confluent (Kafka), Databricks (Spark), and Lightbend (Scala) for consulting, training, and implementation. Their goal is to help enterprises, governments, and global technology companies unlock value from data by building scalable, reliable pipelines and AI workloads.
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
Sydney, Australia
Founded
2008
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Simplify's Take
What believers are saying
- Simple Machines listed 19 open roles on 2026-08-07, signaling active demand.
- DataEngBytes 2025 gold sponsorship on 2025-06-12 raised visibility among Oceania data buyers.
- Simple Machines added senior leadership across ANZ, UK, and Poland during 2026 hiring.
What critics are saying
- Consulting revenue depends on billable utilization; 19 openings pressure delivery if hires lag.
- Confluent and Databricks partnerships expose Simple Machines to vendor-led services competition by 2027.
- Without proprietary products, a referral slowdown from Databricks or Confluent would crush growth.
What makes Simple Machines unique
- Simple Machines combines data architecture, engineering, software, and AI delivery across Sydney, London, Christchurch.
- Its 2026 partner stack spans Confluent, Databricks, Snowflake, AWS, Azure, GCP, and Immuta.
- Jason Martin returned as CTO on 2025-06-12, sharpening its agentic-AI positioning.
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Benefits
- Hybrid Work Options