Senior Data Architect Engineer (SaaS)

TeamBuilder is a rapidly growing healthcare SaaS company on a mission to transform healthcare with innovative technology. They are seeking an experienced Senior Data Engineer / Data Architect to lead the design and development of their enterprise data platform, ensuring the delivery of high-quality data solutions that support operational reporting and advanced analytics.

Responsibilities:

• Design and evolve the organization's data architecture to support operational, analytical, and AI-driven workloads
• Define and implement scalable data warehouse, data lake, and lakehouse architectures
• Establish data modelling standards, governance practices, and architectural best practices
• Design data structures and integration patterns that support long-term scalability, performance, and maintainability
• Drive data platform modernization initiatives leveraging Azure cloud technologies
• Design, develop, and maintain scalable ETL/ELT pipelines that ingest, transform, validate, and deliver data from multiple internal and external systems
• Build robust data integration solutions using Azure data services and modern data engineering frameworks
• Implement monitoring, alerting, and data quality controls to ensure reliable data operations
• Automate data processing workflows and reduce operational overhead through engineering best practices
• Optimize SQL queries, data pipelines, and analytical workloads for performance, scalability, and cost efficiency
• Analyze and improve large-scale datasets and reporting environments
• Identify bottlenecks and implement solutions that improve system responsiveness and data availability
• Partner with engineering teams to improve database design, indexing strategies, and query performance
• Establish data validation, reconciliation, and auditing processes to ensure trusted reporting outcomes
• Investigate and resolve complex data discrepancies across source systems and analytical platforms
• Develop repeatable controls and monitoring processes that improve confidence in business reporting
• Define and maintain data quality standards across the platform
• Design and support data models that power reporting and analytics solutions
• Collaborate with business stakeholders to understand analytical requirements and translate them into scalable data solutions
• Support Power BI and custom analytics platforms through semantic modelling, data optimization, and performance tuning
• Enable self-service analytics through well-designed and governed datasets

Requirements:

• 7+ years of experience in Data Engineering, Data Architecture, or related disciplines
• Strong experience designing and implementing enterprise-scale data architectures
• Expert-level SQL skills with proven experience optimizing complex queries and large datasets
• Extensive experience building ETL/ELT solutions in cloud-based environments
• Strong understanding of data warehousing, dimensional modelling, and analytical data design
• Experience implementing data quality, governance, lineage, and reconciliation processes
• Strong analytical and problem-solving skills with the ability to diagnose complex data issues
• Excellent written and verbal communication skills
• Ability to work independently and collaborate effectively across technical and non-technical teams
• Azure SQL Database
• Azure Data Factory
• Azure Synapse Analytics and/or Azure Databricks
• SQL Server and advanced SQL optimization
• Data Warehouse and Lakehouse design
• ETL/ELT architecture and implementation
• Data modelling (Star Schema, Snowflake, Dimensional Modelling)
• Performance tuning and query optimization
• Data quality and reconciliation frameworks
• Power BI data modelling and performance optimization
• Microsoft Fabric
• Azure Data Lake Storage
• Apache Spark
• Python
• CI/CD for data platforms
• Infrastructure as Code
• Real-time and streaming data architectures
• AI and machine learning data platform experience
• Experience supporting SaaS platforms with large-scale operational and analytical datasets
• Experience working in healthcare, workforce management, scheduling, or other data-intensive industries
• Experience designing data platforms that support advanced analytics, forecasting, optimization, or AI initiatives
• Experience delivering enterprise reporting and business intelligence solutions