Senior Data Platform Engineer

Who We Are 

IgniteData is a thriving, cutting-edge technology business shaping the future of clinical trials in collaboration with some of the largest global pharmaceutical and healthcare organizations globally. 

Clinical trials are complex data collection projects, with a significant amount of information still manually copied from patient Electronic Health Records into the systems used by researchers to run studies. Archer, IgniteData's Source-to-EDC platform, has the potential to transform clinical trial delivery globally by reducing manual data entry and its associated costs, accelerating trials, and ultimately helping new treatments reach patients faster. 

IgniteData is already recognized by leading pharmaceutical organizations as an innovator in the rapidly evolving Source-to-EDC market. Our strategy is to continue expanding our footprint across the the globe while building the scalable technology and data capabilities required to support that growth. 

Your Next Challenge 

We are seeking a hands-on Senior Data Platform Engineer to work closely with our VP of Engineering to bring IgniteData's initial data warehouse and data lake capabilities into production. 

The primary challenge will be designing and implementing a scalable, secure, and maintainable data platform using Microsoft Fabric. You will integrate data from multiple operational and business systems, establish reliable data pipelines and models, and create the technical foundation for trusted reporting and analytics across IgniteData. 

Because this is an emerging capability, the role will initially include responsibility for building Power BI reports and semantic models. The successful candidate must be comfortable working across both data engineering and analytics, but the long-term emphasis of the role will remain on platform architecture, data integration, automation, scalability, and reliability. 

You will be joining at a formative stage, with the opportunity to influence the architecture, engineering standards, development practices, and future direction of IgniteData's enterprise data platform. 

Key Responsibilities 

Data Platform Architecture and Engineering 

• Work with the VP of Engineering to define and implement IgniteData's Microsoft Fabric data platform architecture. 

• Bring the initial data warehouse and data lake environment from early development into a secure, reliable, and supportable production service. 

• Establish scalable data architecture patterns, including appropriate raw, curated, and consumption layers. 

• Design data structures that support operational reporting, executive analytics, customer reporting, and future advanced analytics use cases. 

• Make pragmatic architecture decisions that balance immediate business value with long-term scalability. 

Data Integration and Pipelines 

• Work with engineering team to build automated and reusable data pipelines that ingest information from IgniteData's application, operational, financial, customer, and other business systems. 

• Integrate data from relational databases, APIs, SaaS platforms, structured files, and other internal or external sources. 

• Develop reliable incremental loading, change detection, reconciliation, and error-handling processes. 

• Transform source data into consistent, documented, and analytics-ready datasets. 

• Reduce reliance on manual extracts, spreadsheet manipulation, and one-off reporting processes. 

• Design data ingestion patterns that can accommodate new data sources without requiring significant rework. 

Data Modeling and Quality 

• Develop scalable warehouse and lakehouse data models using appropriate dimensional and relational modeling techniques. 

• Define common business entities, metrics, relationships, and calculation logic across data sources. 

• Implement automated data validation, quality checks, reconciliation, and exception reporting. 

• Establish clear data lineage and traceability from source systems through reports and dashboards. 

• Partner with business stakeholders to ensure that metrics are consistently defined and trusted. 

Reporting and Business Intelligence 

• Build the initial Power BI semantic models, reports, and dashboards required to demonstrate value from the data platform. 

• Translate business reporting requirements into reusable data products rather than isolated reports. 

• Develop clear, performant, and maintainable Power BI datasets and measures. 

• Support reporting for Product, Engineering, Operations, Customer Success, Finance, and executive leadership. 

• Create reporting standards and reusable components that allow the BI capability to scale over time. 

• Help determine which reporting work should remain centralised and which can safely be enabled through governed self-service analytics. 

Production Readiness and Operations 

• Implement monitoring, logging, alerting, and operational support processes for data pipelines and platform components. 

• Establish development, testing, deployment, and release-management practices for the data platform. 

• Use source control, automated deployment, and CI/CD practices wherever practical. 

• Document platform architecture, data models, data pipelines, metric definitions, and operational procedures. 

• Support troubleshooting and root-cause analysis when data or reporting issues arise. 

• Ensure that the platform can be supported by the wider Engineering organisation and does not depend on undocumented individual knowledge. 

Security and Governance 

• Apply appropriate access controls, workspace structures, data classifications, and separation of environments. 

• Work with Engineering, Security, and business stakeholders to ensure data is handled in accordance with IgniteData policies and contractual obligations. 

• Incorporate privacy, security, auditability, retention, and governance requirements into the platform architecture. 

• Support the development of clear ownership and stewardship for critical datasets and business metrics. 

The Successful Candidate Will Need to Demonstrate 

• Significant professional experience in data engineering, data platform engineering, or a closely related role. 

• Experience designing and delivering a production data warehouse, data lake, or lakehouse environment. 

• Hands-on experience with Microsoft Fabric, including several of the following: OneLake; Fabric Lakehouse and Warehouse; Data Factory pipelines; Fabric notebooks; Power BI; semantic models; and data flows. 

• Strong SQL skills and experience designing performant data transformations and models. 

• Experience with Python, PySpark, or another language commonly used for data engineering. 

• Strong understanding of dimensional modeling, data warehousing principles, and analytics-oriented data design. 

• Experience integrating data from databases, APIs, SaaS applications, flat files, and other heterogeneous sources. 

• Experience implementing incremental loads, pipeline orchestration, error handling, monitoring, and data-quality controls. 

• Practical experience with Power BI, including data modeling, DAX, report development, performance optimization, and row-level security. 

• Familiarity with Git, CI/CD, automated deployments, and modern software engineering practices. 

• Understanding of cloud security, role-based access, data governance, and environment management. 

• Strong analytical and problem-solving skills, including the ability to diagnose complex data issues across multiple systems. 

• The ability to work independently, make sound technical decisions, and deliver in an evolving environment. 

• Strong communication skills and the ability to translate between technical implementation and business requirements. 

What Success Looks Like 

During the first 12 months, the successful candidate will have: 

• Established a production-ready Microsoft Fabric environment with clear development, testing, and production practices. 

• Automated ingestion from IgniteData's initial priority data sources. 

• Implemented scalable and documented warehouse or lakehouse data models. 

• Delivered trusted Power BI reports that provide visible business value while using reusable semantic models and governed metrics. 

• Introduced monitoring, data-quality controls, lineage, and operational support processes. 

• Reduced dependency on manually assembled reports, spreadsheets, and one-off data extracts. 

• Developed a clear technical roadmap for expanding the platform as IgniteData's products, customers, and reporting requirements grow. 

Information Security Responsibilities 

All IgniteData employees are responsible for completing required security training, adhering to applicable security policies and procedures, and supporting the organization's information security requirements. 

What You Get in Return 

A competitive salary, dependent on experience, together with a comprehensive benefits package and the opportunity to play a foundational role in building a strategically important capability within a rapidly growing clinical trial technology company. 

This is a full-time position. 

Diversity & Inclusion 

IgniteData is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to age, colour, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, political affiliation, status as an individual with a physical or mental disability, status as an individual with a protected veteran status, race, religion, sex, including pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations, and ordinances. 

We celebrate diversity and hire on the basis of competence, performance, and business needs.