Senior Data Reliability Engineer

SS&C Blue Prism allows organisations to deliver transformational business value via our intelligent automation platform. We make products with one aim in mind - to improve experiences for people. By connecting people and digital workers, you can use the right resource, every time, for the best customer and business outcomes. We supply enterprise-wide software that not only provides full control and governance, but also allows businesses to react fast to continuous change.

We apply SRE principles to everything we build — including our data platform. This role owns the reliability, quality, and scalability of our internal data ecosystem, bringing the same rigour (SLIs/SLOs, observability, incident response, automation) that traditional SREs apply to application services, but focused entirely on data systems. As our Senior Data Reliability Engineer, you will design data models, build transformation pipelines, create dashboards, and enable self-service analytics — all with production-grade reliability baked in from the start. You will be the person who ensures our data is trustworthy, timely, and accessible, and that we know immediately when it isn’t.

What Success Looks Like In your first year, you will:

• Consolidate fragmented data sources into a well-modelled, reliable data platform on Azure
• Build production-grade ETL/ELT pipelines with monitoring, alerting, and automated recovery
• Create Power BI dashboards and reports that give stakeholders operational visibility they can trust
• Define and enforce SLOs for data freshness, accuracy, and availability
• Enable self-service analytics so teams can answer their own questions without waiting on you
• Establish data quality standards and automated testing that catch issues before they reach reports
• Reduce manual reporting overhead through automation

What You Will Do:

• Design data models (dimensional, star schema, or appropriate patterns) that serve reporting and analytics needs
• Build and maintain ETL/ELT pipelines using Azure Data Factory, integrating internal and external data sources
• Write and optimise SQL transformations for performance, cost, and clarity
• Apply reliability engineering to every pipeline: error handling, retry logic, dead-letter queues, and graceful degradation
• Ensure data quality, integrity, and consistency through automated testing and validation
• Troubleshoot and resolve pipeline failures and data inconsistencies with proper incident response

Observability & Incident Response for Data Systems:

• Define SLIs/SLOs for data services: freshness, completeness, accuracy
• Implement monitoring and alerting for pipeline health, data quality drift, and report refresh status
• Build observability into the platform so problems surface before users notice them
• Lead incident response for data-related issues
• Conduct blameless post-mortems and feed learnings back into platform improvements
• Join the out-of-hours on-call rota once suitably trained

Reporting & Analytics Enablement:

• Build and maintain Power BI dashboards and reports for operational and strategic decision-making
• Partner with stakeholders to understand their questions and translate them into reliable data solutions
• Design the semantic layer and data models within Power BI
• Enable self-service analytics by providing clean, documented, well-governed data
• Establish a reporting platform that scales reliably as the organisation grows

DataOps & Automation:

• Automate repetitive data processes using Python, SQL, and Azure-native tooling
• Implement CI/CD for data pipelines and reporting assets
• Apply toil-reduction thinking
• Manage data infrastructure as code where appropriate
• Build reusable frameworks that raise the reliability baseline across all data services

Cross-Functional Collaboration:

• Act as the bridge between technical teams and business stakeholders
• Contribute to SRE practices and reliability culture across the wider organisation
• Work with teams to understand their data needs and deliver solutions that meet defined service levels
• Promote data literacy and help non-technical colleagues become confident with self-service tools

What You Will Bring:

• 5+ years in Data Engineering, Analytics Engineering, or data-focused SRE/DevOps roles
• Strong SQL skills
• Hands-on experience with data modelling
• Production experience building and maintaining data pipelines
• Hands-on Power BI development
• Python scripting for data transformation, automation, and pipeline development
• Experience implementing monitoring and observability for data systems
• Experience working with stakeholders to translate business needs into data solutions
• Understanding of SRE principles
• Familiarity with cloud data platforms

Preferred Experience:

• Building or consolidating a data platform from fragmented sources
• Familiarity with DataOps practices
• Experience with data quality frameworks
• Knowledge of data governance and cataloguing practices
• Infrastructure as Code for data infrastructure
• Experience with Docker and Kubernetes in data platform contexts
• Familiarity with modern transformation tools
• Familiarity with AI tooling

Why You Will Love It Here!

• Your Future: Professional Development Reimbursement including access to SS&C University
• Work/Life Balance: Competitive holiday scheme
• Your Wellbeing: Competitive benefits designed to support the wellbeing of our staff
• Diversity & Inclusion: Committed to Welcoming, Celebrating and Thriving on Diversity
• Training: Hands-On, Team-Customised throughout your career

We encourage applications from people of all backgrounds to enable us to bring diverse perspectives to our thinking and conversation. It's important to us that we strive to have a workforce that is diverse in the widest sense.