SS&C Technologies
Senior Data Reliability Engineer
England
Posted 9 days ago
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Senior Data Reliability Engineer
Senior Data Reliability Engineer
Locations: UK Remote
SS&C Blue Prism is an intelligent automation platform that delivers transformational business value by connecting people and digital workers to optimize customer outcomes and growth. This role focuses on the reliability, quality, and scalability of our internal data platform within an SRE culture, ensuring production-grade data systems.
About the Role
- You will apply SRE principles to data systems, consolidating fragmented pipelines and introducing observability, SLIs, SLOs, and incident response for data.
- Own end-to-end data reliability, enabling timely, trustworthy, and accessible data across the organization.
- Work on an Azure-centric stack (Azure Data Factory, Synapse, Azure SQL, Power BI) with a focus on data modelling, transformation pipelines, and self-service analytics.
Your Daily Work
A typical week may involve:
- Designing and consolidating customer data models from three systems into a single reliable reporting view.
- Investigating a data freshness SLO breach, diagnosing failures, fixing root causes, and adding alerting.
- Building a Power BI dashboard with stakeholder input for operational KPIs.
- Addressing schema drift issues and data quality test results through automation.
- Writing Python scripts to replace manual, time-consuming extracts.
- Partnering with Operations to enable self-service analytics.
- Leading blameless post-mortems (on-call expected ~1x/3–4 weeks once trained).
What Success Looks Like (First Year)
- Consolidate fragmented data sources into a scalable Azure data platform.
- Build observability-driven ETL/ELT pipelines with automation, alerting, and recovery.
- Deliver reliable Power BI dashboards trusted by business stakeholders.
- Define SLIs/SLOs for data freshness, accuracy, and availability.
- Automate repetitive tasks, reducing toil and manual reporting overhead.
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Responsibilities
Data Pipeline Reliability & Development
- Design and maintain robust data models (dimensional, star schemas).
- Develop ETL/ELT pipelines (Azure Data Factory, SQL) for internal/external data.
- Optimise and validate complex SQL transformations.
- Implement error handling, retries, dead-letter queues for pipeline reliability.
- Ensure data consistency through automated validation and testing.
- Troubleshoot data inconsistencies and failures via structured incident response.
Observability & Incident Response
- Define SLIs/SLOs (freshness, completeness, accuracy) for data services.
- Deploy monitoring and alerts for pipeline/quality/availability.
- Build observability to proactively preempt issues.
- Lead incident rotation, including blameless post-mortems.
- Contribute to cross-team reliability practices.
Reporting & Analytics Enablement
- Build and optimise Power BI dashboards and reports.
- Align with stakeholders to translate needs into self-service data solutions.
- Design DAX models, relationships, and row-level security.
- Establish a scalable, governed reporting platform.
DataOps & Automation
- Automate data processes with Python, SQL, and Azure tooling.
- Implement CI/CD pipelines (version control, testing, deployment).
- Adopt toil-reduction principles (automate manual tasks twice).
- Use Infrastructure as Code (Terraform, Bicep) for replayable deployments.
- Develop reusable reliability frameworks for all data services.
Cross-Functional Collaboration
- Bridge technical/data teams with business stakeholders.
- Advocate for data literacy and self-service adoption.
- Collaborate on reliability culture at scale.
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Requirements
Technical Experience
- 5+ years in Data Engineering, Analytics Engineering, or SRE/DevOps (data-focused).
- Expert-level SQL (querying, transformation, performance optimisation).
- Hands-on data modelling (dimensional/star schemas).
- Production pipeline experience (Azure Data Factory preferred; e.g. Airflow, Spark).
- Power BI (reports, DAX, data models, publishing).
- Python (data automation/scripting/pipelines).
- Observability in data systems (monitoring, alerting).
- Stakeholder alignment (translating business needs into data solutions).
- SRE awareness: familiarity with SLIs, SLOs, error budgets, incident analysis.
Preferred Knowledge
- Consolidating fragmented data platforms.
- DataOps (CI/CD, pipeline automation/testing).
- Data quality frameworks (Great Expectations, dbt tests).
- Infrastructure as Code (Terraform, Bicep, ARM).
- Kubernetes/Docker in data platform environments.
- Modern data tools (e.g. data build tool, dbt, AI tools).
Soft Skills & Values
- Problem-solving with structured reliability instincts.
- Ownership: embracing data as a "system" that must be trusted.
- Collaboration across teams with varied technical/business priorities.
Benefits & Culture
- Professional development: Access to SS&C University and grant reimbursement.
- Wellbeing: Competitive benefits (e.g., holiday, mental health support).
- Diversity & Inclusion: Commitment to fostering lived-in diversity.
- On-growth: Customised training tailoured to your career path.
SS&C Blue Prism is proud to promote diversity and welcomes applications from all backgrounds. For more details, explore our opportunities at www.ssctech.com/careers.
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Skills
Data Engineering
Analytics Engineering
SQL
Data Modelling
ETL
ELT
Power BI
Python
Monitoring
Observability
Incident Response
Data Quality
Data Governance
Cloud Data Platforms
DataOps
Automation
Location