Data Engineer; Exclusive

Position: Staff Data Engineer (Exclusive)
Staff Data Engineer Exclusive to Ocho People, you won't find this role advertised anywhere else Staff-level, genuinely hands-on data engineering role, still building and shipping production systems, not advising from the sidelines £110,000, Belfast, remote hybrid working Own end-to-end data platforms at genuinely global scale, for a business used by some of the world's best-known consumer brands Deep, modern distributed data stack:
Spark, Kafka, dbt, Airflow/Dagster, cloud-native architecture About the Company This is an exclusive search with Ocho People for a well-established, global technology business operating at genuinely large scale. It works with a large network of well-known brands and retailers, helping them turn customer feedback into real commercial insight, and operates across multiple continents with a strong international footprint. It's an independently certified Great Place to Work in several countries, including the UK.

The Role This isn't a purely strategic or advisory Staff role. You'll join the Insights team as someone who has personally designed, built and scaled complex data systems, and still enjoys getting into the technical detail rather than handing it off. You'll own data pipelines and platforms end to end: from requirements through architecture, implementation, deployment and optimisation, making and defending real technical decisions along the way rather than producing target-state diagrams for someone else to build.

You'll work closely with cross-functional teams to understand what the data actually needs to do, while staying close enough to the code and the infrastructure to be the person who can say "I built this, here's why, and here's what it delivered."

Key Responsibilities Design, build and personally ship large-scale, distributed data pipelines and platforms, not just target architectures or recommendations Own the full lifecycle end to end: requirements, architecture, implementation, deployment and ongoing optimisation Make and defend real technical trade-off decisions: which database, which file format, which orchestration tool, batch versus streaming, and why Build and operate distributed data processing with Spark, working directly with how it behaves under real load, not just listing it as a skill Apply modern judgement to data modelling, knowing when dimensional and star modelling still earns its place and when a modern platform changes the rules Optimise for query performance, partitioning, indexing and cost as data volumes and complexity grow Embed strong software engineering practice into data work: testing, CI/CD, version control and containerisation Collaborate with cross-functional teams to translate real business and product requirements into production-grade systems Troubleshoot and resolve issues directly in live, large-scale data systems Mentor others on the team while staying hands-on yourself, an architect who still builds What You'll Need Essential: 7 years personally designing and building robust, scalable, distributed data systems and pipelines in production, not primarily advisory or data strategy work Strong, genuinely hands-on Spark and distributed processing experience, with a real understanding of how it behaves at scale, not just on a CV Experience across a modern data stack: dbt, SQL, Athena/Trino, Redshift or Snowflake, and RDBMSs such as PostgreSQL or MySQL

Experience with data orchestration tools such as Apache Airflow or Dagster Knowledge of event-driven architectures and streaming technologies such as Apache Kafka, Kafka Streams or Apache Flink

Experience with public cloud environments (AWS, GCP or Azure) and infrastructure as code such as Terraform Strong software engineering practice: testing, CI/CD (Jenkins or…