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Principal Data Platform Engineer

Simple Machines
Sydney NSW

Quick Apply

Job Details

Qualifications

CI/CD
Data modelling
Cassandra
NoSQL
Google Cloud Platform
MongoDB
SQL
AWS
PostgreSQL
Terrafrom
Data pipeline
GitHub

Full Job Description

Principal Data Platform Engineer

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 life™.

Requirements

The Role

This is a hands-on principal engineering role, not an architecture-only seat and not a support function. You’ll be responsible for technical direction, platform design and architectural decision-making.

You'll design and build greenfield data platforms, real-time pipelines, and data products for clients who are serious about using data properly. You’ll work in small, high-calibre teams and operate close to both the problem and the client.

If you enjoy solving hard data problems, shaping modern architectures (data mesh, data products, contracts), and delivering real outcomes — this is your lane.

What You’ll Be Doing

Lead Platform & Architecture Design

Own the end-to-end architecture of modern, cloud-native data platforms
Design scalable data ecosystems using data mesh, data products, and data contracts
Make high-impact architectural decisions across ingestion, storage, processing, and access layers
Ensure platforms are secure, compliant, and production-grade by design

Build Modern Data Platforms

Design and deliver cloud-native data platforms using Databricks, Snowflake, AWS, and GCP
Apply modern architectural patterns: data mesh, data products, and data contracts
Integrate deeply with client systems to enable scalable, consumer-oriented data access

Develop High-Performance Pipelines

Build and optimise batch and real-time pipelines
Work with streaming and event-driven tech such as Kafka, Flink, Kinesis, Pub/Sub
Orchestrate workflows using Airflow, Dataflow, Glue

Work at Scale

Process and transform large datasets using Spark and Flink
Design systems that perform in production - not just on paper

Own Data Storage & Performance

Work across relational, NoSQL, and analytical stores (Postgres, BigQuery, Snowflake, Cassandra, MongoDB)
Optimise storage formats and access patterns (Parquet, Delta, ORC, Avro)

Cloud, Security & Governance

Implement secure, compliant data solutions with security by design
Embed governance without killing developer velocity

Consult and Influence

Work directly with clients to understand problems and shape solutions
Translate business needs into pragmatic engineering decisions
Act as a trusted technical advisor, not just an order taker

Technical Leadership & Quality

Set engineering standards, patterns, and best practices across teams
Review designs and code, providing clear technical direction and mentorship
Raise the bar on data quality, testing, observability, and operational excellence

What We’re Looking For

Core Engineering Strength

Strong Python and SQL
Deep experience with Spark and modern data platforms (Databricks / Snowflake)
Solid grasp of cloud data services (AWS or GCP)

Architecture & Design Judgement

Demonstrated ownership of large-scale data platform architectures
Strong data modelling skills and architectural decision-making ability
Comfortable balancing trade-offs between performance, cost, and complexity

Data Platform Experience

Built and operated large-scale data pipelines in production
Strong data modelling capability and architectural judgement
Comfortable with multiple storage technologies and formats

Engineering Discipline

Infrastructure-as-code experience (Terraform, Pulumi)
CI/CD pipelines using tools like GitHub Actions, ArgoCD
Data testing and quality frameworks (dbt, Great Expectations, Soda)

Delivery & Consulting Mindset

Experience in consulting or professional services environments
Strong consulting instincts — able to challenge assumptions and guide clients toward better outcomes
Comfortable mentoring senior engineers and influencing technical culture

Benefits

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.

Quick Apply

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