Senior data reliability engineer Work, Jobs in Remote (with Salaries)

Senior Data Reliability Engineer
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- Full-time
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Senior Software Engineer - Grafana Databases, Managed Services | UK | Remote
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Senior Data Reliability Engineer

SS&C Technologies -
Remote

Apply Now

Job details

Full-time

Qualifications

Power BI
Data modelling
Azure
Kubernetes
DevOps
Test automation
SQL
Docker
C
Terraform
Data pipeline
IT
AI
Python

Full job description

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.

Job Description

SS&C Blue Prism

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.

Exceed customer expectations, stay competitive, accelerate growth.

Senior Data Reliability Engineer

Locations : UK Remote

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 . We have early-stage foundations in place: some pipelines and tooling exist, but they’re fragmented and need consolidation, proper architecture, and the reliability engineering mindset this role will bring. Our stack is Azure-centric (Azure Data Factory, Synapse Analytics, Azure SQL, Power BI).

This role sits within our SRE culture but is focused specifically on data systems. You’ll contribute to reliability practices across the organisation , but your day-to-day domain is the data platform — not application infrastructure. We have a separate platform team responsible for Kubernetes, service mesh, and application deployment pipelines. We’re looking for someone who understands what the data means , not just the infrastructure it runs on.

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 — not just pipelines that work, but pipelines that tell you when they don’t

Create Power BI dashboards and reports that give stakeholders operational visibility they can trust

Define and enforce SLOs for data freshness, accuracy, and availability — treating data as a service with clear reliability targets

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, applying toil-reduction principles from SRE to data operations

What You Will Do

Data Pipeline Reliability & Development

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 (how recent), completeness (how much), accuracy (how correct)

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 — diagnose root causes and implement lasting fixes, not just restarts

Conduct blameless post-mortems and feed learnings back into platform improvements

Join the out-of-hours on-call rota (typically once every 3–4 weeks) 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 (DAX, relationships, row-level security)

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 (version control, testing, deployment)

Apply toil-reduction thinking: if you’re doing it manually more than twice, automate it

Manage data infrastructure as code where appropriate ( Terraform, Bicep, or ARM templates)

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 — you think in SQL and can write complex, performant queries and transformations

Hands-on experience with data modelling (dimensional modelling, star schemas, or equivalent patterns)

Production experience building and maintaining data pipelines (Azure Data Factory preferred, or similar orchestration tools)

Hands-on Power BI development: building reports, DAX measures, data models, and published dashboards

Python scripting for data transformation, automation, and pipeline development

Experience implementing monitoring and observability for data systems (not just application infrastructure)

Experience working with stakeholders to translate business needs into data solutions

Understanding of SRE principles: SLIs/SLOs, error budgets, incident response, blameless post-mortems

Familiarity with cloud data platforms (Azure preferred: Synapse Analytics, Azure SQL, Azure Data Lake)

Preferred

Experience building or consolidating a data platform from fragmented sources

Familiarity with DataOps practices: CI/CD for data assets, automated testing, version-controlled pipelines

Experience with data quality frameworks (Great Expectations, dbt tests, or equivalent)

Knowledge of data governance and cataloguing practices

Infrastructure as Code for data infrastructure (Terraform, Bicep)

Experience with Docker and Kubernetes in data platform contexts

Familiarity with modern transformation tools ( dbt or similar)

Familiarity with AI tooling and experience using it to enhance productivity

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.

Thank you for your interest in SS&C! If applicable, to further explore this opportunity, please apply directly with us through our Careers page on our corporate website @ www.ssctech.com/careers .

Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.

Applications will be accepted on an ongoing basis until the position is filled.

SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.

Apply Now

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senior data reliability engineer jobs in remote

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