Who We Are
Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, Poland and San Francisco. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of Data Engineering, Software Engineering and AI.
We work with enterprises, scale-ups, and government to turn messy, high-value data into products, platforms, and decisions that actually move the needle.
We don't do generic. We build things that matter - We engineer data to lifeTM.
The Role
You will be the interface between product owners, managers, and implementation team to support the design and delivery of compelling market leading solutions. Data and software solutions delivery is a team sport.
You will play a critical role in that team by:
* Match innovative yet practical data solutions to our customers' thorniest problems, building on a foundation of strong engineering and operational practices.
* Balance multiple factors in the delivery of solutions including: effectiveness, cost, reliability, risk, safety, stakeholder needs, and so on.
* Capturing and presenting back, through documentation, presentations, and proofs of concept, the essential requirements of a solution.
* Translating the essential requirements into a number of alternative design approaches, which may include options to build or buy solution components.
* Helping the client navigate the process of selecting the best solution and
* Elaborating on the chosen solution to a level that facilitates detailed project planning, technology selection, and. documentation of key interfaces.
* Linking technology components to process, organisational, and change management dependencies to ensure success of the total solution.
* Thinking outside the box and staying focused on the essential business needs.
Essential skills:
1. Knowledge of the key data and infrastructure services in each of the major cloud providers including the Google Cloud Platform, Amazon, and Azure.
2. Knowledge of one or more programming languages.
3. Experienced in data modelling and key data warehousing concepts including
alternative database schemas (SQL and "NoSQL"), database normal forms,
dimensional models, slowly changing dimensions, metadata management, Lambda and Kappa architectures, etc.
4. At least a foundational knowledge of machine learning including ability to describe a basic classification algorithm and key components of machine learning operations.
5. Knowledge of one or more architectural frameworks and containerisation strategies including Kubernetes.
6. Knowledge of DevOps processes and event-driven architectures.
The experience you will have:
* Experience in a professional services role - delivering a solution to a third-party client with an agreed budget and schedule.
* Preferred additional experience in an enterprise, start-up, or sales engineering role.
* Experience in a team delivering a bespoke solution involving custom development or custom integration.
* Design and implementation of a strategic data platform that involved a change over the previous data architecture.
* Experience with "Big Data" platforms and technologies such as Hadoop, Redshift, BigQuery, Snowflake, Databricks, etc.
* Experience with implementing a large data platform in a cloud environment.
* Experience with a project involving advanced analytics such as a statistical or machine learning model.
* Experience in teams employing Agile and DevOps practices.
Why Simple Machines
* You'll work on interesting, high-impact problems
* You'll build modern platforms, not maintain legacy mess
* You'll be surrounded by senior engineers who actually know their craft
* You'll have autonomy, influence, and room to grow
If you're a senior data engineer who wants to build properly, think clearly, and deliver real outcomes - we should talk.
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