Senior Data Engineer

Simple Machines; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Simple Machines is seeking a Senior Data Engineer to lead hands-on architecture and delivery of modern, cloud-native data platforms. You’ll design and build real-time pipelines, data products, and data contracts for high-value client projects, working in small, high-calibre teams close to problems and clients.

You’ll influence architectural decisions across ingestion, storage, processing, and access layers, ensuring secure, production-grade platforms and scalable data access across client

Qualifications

• Proven experience designing and delivering modern data platforms.
• Strong track record of building data pipelines and data platforms in production.
• Ability to translate business needs into pragmatic engineering solutions.

Responsibilities

• Own end-to-end architecture of cloud-native data platforms.
• Design scalable data ecosystems with data mesh, data products, and data contracts.
• Make architectural decisions across ingestion, storage, processing and access layers.
• Ensure platforms are secure, compliant, and production-grade by design.
• Design and deliver cloud-native data platforms with Databricks, Snowflake, AWS, and GCP.
• Apply modern patterns like data mesh and data contracts.
• Integrate with client systems for scalable data access.
• Build and optimize batch and real-time pipelines.
• Work with streaming tech: Kafka, Flink, Kinesis, Pub/Sub.
• Orchestrate with Airflow, Dataflow, Glue.
• Process large datasets with Spark and Flink.
• Design production-grade storage across Postgres, BigQuery, Snowflake, Cassandra, MongoDB.
• Optimize storage formats: Parquet, Delta, ORC, Avro.
• Implement security by design and governance.
• Guide clients with trusted technical advice.
• Set engineering standards and review designs.

Skills

Python

SQL

Spark

Databricks

Snowflake

AWS

GCP

Data mesh

Data contracts

Data modelling

Cloud architectures

Tools

Terraform

Pulumi

GitHub Actions

ArgoCD

dbt

Great Expectations

Soda

Airflow

Kubernetes

Kafka

Job description

Senior Data Engineer

Who We Are

Simple Machines is a global, independent technology consultancy operating across Sydney, New Zealand, London, and Poland. We design and build modern data platforms, intelligent systems, and bespoke software at the intersection ofData Engineering, Software EngineeringandAI.

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 be responsible for technical direction, platform design and architectural decision-making.

You’ll design and buildgreenfield 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 usingdata 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 usingDatabricks, 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 optimisebatch and real-time pipelines
• Work with streaming and event-driven tech such asKafka, Flink, Kinesis, Pub/Sub
• Orchestrate workflows usingAirflow, Dataflow, Glue

Work at Scale

• Process and transform large datasets usingSpark 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 withsecurity 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

• StrongPython and SQL
• Deep experience withSparkand 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 operatedlarge-scale data pipelinesin 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 likeGitHub 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

BenefitsWhy Simple Machines

• You’ll work oninteresting, high-impact problems
• You’ll buildmodern 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