Asks for

The ad says“Experience designing platforms and architectures to support AI-native use cases, machine learning systems, agentic workflows, and intelligent software platforms”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Demonstrated experience architecting and delivering modern cloud-native data platforms at enterprise scale”
The ad says“10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture”
The ad says“10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture”
The ad says“Deep understanding of data mesh principles, federated governance, and scalable domain-oriented data ownership models”
The ad says“10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Deep understanding of data mesh principles, federated governance, and scalable domain-oriented data ownership models”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Strong understanding of real-time and event-driven architectures, including streaming data systems and low-latency processing patterns”
The ad says“Experience designing platforms and architectures to support AI-native use cases, machine learning systems, agentic workflows, and intelligent software platforms”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Strong pre-sales, proposal development, and solution shaping capability”
The ad says“Strong pre-sales, proposal development, and solution shaping capability”
The ad says“Strong understanding of real-time and event-driven architectures, including streaming data systems and low-latency processing patterns”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Strong pre-sales, proposal development, and solution shaping capability”
The ad says“Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling”
The ad says“Strong understanding of real-time and event-driven architectures, including streaming data systems and low-latency processing patterns”

We are looking for a senior data leader to join Simple Machines in London as part of our Global Data Practice leadership team
This is a strategic and hands-on leadership role focused on helping shape the future direction of our data platform capability across the UK and Europe
The individual will play a key role in defining our propositions, strengthening our technical capability, and helping clients modernise their data ecosystems for an AI-native future
Part of the Global Data Practice leadership team
Helping define and evolve Simple Machines’ data platform propositions, technical direction, and strategic positioning
Advising enterprise clients on modern data platform strategy, architecture, operating models, and AI readiness
Supporting organisations as they evolve from traditional centralised data platforms toward AI-native, real-time, and data product-oriented operating models
Working closely with Engagement Managers and senior leadership across major strategic initiatives
Leading architecture and technical direction for complex enterprise data platform and transformation programs
Acting as a senior technical counterpart across strategic client engagements and partner relationships
Pre-sales, proposal development, technical solution shaping, and executive stakeholder engagement
Building trusted relationships with strategic technology partners and staying current with emerging platform capabilities and market direction
Supporting recruitment, mentoring, capability uplift, and practice development across the broader engineering organisation
Leading major client initiatives across data engineering, platform modernisation, AI enablement, and operational data systems
Contributing to thought leadership, market positioning, and growth initiatives across the UK and Europe

Benefits

Employee assistance programme
Generous parental leave: Three months’ fully paid primary carer leave and one month fully paid secondary carer leave, subject to a minimum 12 month tenure
Flexible working: Want to work from home or leave early to pick up the kids? Need to start early some days, later on others? No problem!
“Your day”: One day per year, in addition to annual leave days that you can take off with no explanation required
Upskill - Learning and development: We all love continually learning and have a generous budget for you to upskill, join conferences, get certified and qualified

Preferred experience

We are looking for a leader who understands where enterprise data platforms are heading over the next five years, not where they were five years ago
The role requires someone equally comfortable operating at executive, architectural, commercial, and delivery levels
Strong experience developing solutions centred around data products and reusable enterprise data capabilities
Strong understanding of real-time and event-driven architectures, including streaming data systems and low-latency processing patterns
Experience leading major enterprise initiatives and high-performing engineering teams
Demonstrated experience architecting and delivering modern cloud-native data platforms at enterprise scale
Experience building platforms that support governed, discoverable, reusable, and operationalised data products across large organisations
Deep understanding of data mesh principles, federated governance, and scalable domain-oriented data ownership models
Experience with technologies and ecosystems such as GCP, AWS, Azure, Databricks, Snowflake, Kafka, Spark, dbt, Kubernetes, Airflow, ML/AI enablement, or similar modern platform tooling
Comfortable operating in a fast-moving, high-performance consultancy environment
Familiarity with contemporary data stack technologies and modern engineering practices
Strong pre-sales, proposal development, and solution shaping capability
Strong understanding of platform architecture, distributed data systems, orchestration, governance, and scalable data product design
Experience designing platforms and architectures to support AI-native use cases, machine learning systems, agentic workflows, and intelligent software platforms
10+ years’ experience across data engineering, data platforms, analytics engineering, or data architecture
Proven consultancy and enterprise client-facing experience
Strong commercial acumen and ability to engage credibly with senior technical and business stakeholders
We are looking for someone who combines strong technical depth with commercial and strategic capability. This is not purely a delivery management role, nor is it purely architectural. The ideal person will have a strong point of view on the future of enterprise data platforms, modern data operating models, and the convergence of data engineering and AI enablement
They should be comfortable moving between executive conversations, whiteboarding architecture, shaping proposals, mentoring teams, and helping clients navigate complex transformation programs