Senior Data Platform Engineer at Simple Machines

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

29 Mar, 26

Salary

0.0

Posted On

29 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Spark, Databricks, Snowflake, AWS, GCP, Data Modelling, Infrastructure-as-Code, CI/CD, Data Testing, Kafka, Flink, Airflow, Terraform, Agile

Industry

Information Technology & Services

Description

Senior Data Platform Engineer Simple Machines Hybrid · Full-time · Sydney (ANZ) Who We Are Simple Machines is a global, independent technology consultancy operating across London, Poland, Sydney, San Francisco, and New Zealand. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection of data engineering, AI, and software engineering. 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™. The Role This is a hands-on senior engineering role, not an architecture-only seat and not a support function. 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 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 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) 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) Nice to Have JVM or systems languages (Scala, Java, Go, Rust) Graph or specialised stores (Neo4j, Cassandra) Delivery & Consulting Mindset Experience in consulting or professional services environments Comfortable working in agile teams Able to engage stakeholders and drive outcomes, not just ship code 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.

Responsibilities

The role involves designing and building greenfield data platforms, real-time pipelines, and data products for clients. The engineer will work closely with clients to solve complex data problems and deliver impactful solutions.