Principal Data Solution Architect - Flutter Functions, Hybrid

Principal Data Solution Architect - Flutter Functions, Hybrid

Architect

In Flutter COO we work with experts across Flutter to build, deploy and communicate the Flutter Edge. Together we cover Product & Payments, Technology, Sportsbook Product & Trading, People, Property, Corporate Communications and Strategic Partnerships & Transformation.

We are seeking a Principal Data Solution Architect to design and deliver distributed data platforms that power Flutter's applications across Gaming and Sportsbook. This role is focused on execution and solutions delivery – building scalable, high-performance data platforms that enable real-time and batch data processing at scale. The Principal Data Solution Architect will be responsible for architecting distributed data platforms including real-time streaming infrastructure, distributed compute platforms, object storage solutions, and SQL/NoSQL data stores. You will work closely with application teams, Product, and Engineering to design data solutions that serve business-critical applications, ensuring they can efficiently produce, consume, and process data at Flutter's scale. This role is pivotal to supporting Flutter Functions' data strategy through practical, executable solutions. You will need strong convictions about the right technical approaches for distributed systems, whilst being pragmatic and responsive to the immediate needs of application teams and business stakeholders. Data continues to be a strategic asset for Flutter. Our capability to process, stream, and serve data to applications in real-time is increasingly important as we strive to deliver the most compelling experience to our worldwide customer base across Gaming and Sportsbook.

Key Accountabilities & Responsibilities:

• Drive platform capability improvements - continuously enhance distributed data platforms using knowledge of Spark, Databricks, Kafka, Pulsar, Cassandra, and object stores to maintain best-in-class capabilities

• Enable application data consumption - understand how applications produce and consume data, designing solutions that enable efficient data access patterns, real-time streaming, and batch processing for application needs

• Architect data streaming solutions - design and implement real-time data streaming architectures using Kafka and Pulsar, ensuring low-latency data delivery to downstream applications and services

• Design distributed data structures - work with engineering teams to design effective data structures for distributed systems like Cassandra, optimizing for read/write patterns, scalability, and performance

• Deliver cloud-native data solutions - architect and implement data platforms on AWS leveraging cloud native services, Databricks, object stores (S3), and distributed compute frameworks

• Provide technical leadership and mentoring - mentor engineers and architects on distributed data platform patterns, helping teams deliver robust solutions and grow their technical capabilities

• Develop executable roadmaps - create pragmatic technology roadmaps that deliver near-term business value while progressing toward target state architectures for distributed data platforms

• Partner with engineering teams - build strong relationships with engineering teams across Gaming and Sportsbook, understanding their data needs and translating them into scalable platform solutions

• Design solutions for projects - deliver ADRs, data models, technical designs, and assessments to support delivery of business goals, working with engineering teams to bring solutions to life

• Influence technical strategy - shape the technical direction of data platforms, considering future application requirements and emerging technologies in distributed systems and data streaming

• Manage technology risk - identify, communicate, and mitigate technology risks associated with distributed systems, data platform decisions, and system integrations

• Ensure operational excellence - design solutions with security, cost optimization, performance, regulatory requirements, and compliance in mind

• Contribute to architecture governance - support architecture forums and governance processes, ensuring timely review and alignment across Flutter

• Distributed data platforms expertise – extensive experience designing and implementing distributed data platforms at scale, with deep understanding of distributed systems principles and trade-offs

• Data streaming architecture – proven track record architecting and implementing real-time / low-latency data streaming platforms including patterns for event-driven architectures

• OLTP, NoSQL and distributed databases – experience with Cassandra or similar distributed databases, understanding data structures, partitioning strategies, consistency models, and performance optimization, as well as OLTP databases such as PostgreSQL and MySQL

• Distributed compute frameworks – strong experience with Apache Spark and distributed data processing, including optimisation, performance tuning, and large-scale batch/streaming workloads

• Cloud-native data platforms – demonstrated experience with any Cloud Providers such as AWS, GCP, Azure, including Databricks.

• Application-aware data architecture – strong understanding of how applications produce and consume data, designing platforms that serve application needs efficiently across real-time and batch use cases

• Large-scale platform delivery – track record of delivering large-scale data platforms for high-volume B2C software businesses, preferably in Gaming, Sportsbook, or similar real-time domains

• Data transformation experience – demonstrated experience contributing to data modernisation and migration initiatives and ability to drive a data first approach within the organisation.

• Solutions delivery focus – proven ability to execute and deliver practical solutions, working closely with engineering teams to bring architectures to life

• ML/AI platform enablement - demonstrated experience productionising data science and ML/AI capabilities through the data lifecycle, including feature stores, training pipelines, model serving patterns, and data platforms that enable ML at scale

• Regulatory & compliance experience – designed and implemented compliant data solutions across regulated environments (PCI/SOX/HIPAA), ensuring adherence to industry standards and data protection requirements.