Senior Data Architect Engineer (SaaS)

Summary of Role

We are seeking an experienced Senior Data Engineer / Data Architect to lead the design, development, optimization, and evolution of our enterprise data platform. This is a hands-on senior individual contributor role responsible for architecting scalable data solutions, building robust data pipelines, optimizing analytical workloads, and ensuring the delivery of trusted, high-quality data across the organization.

Key Responsibilities

• Data Architecture & Platform Design
• 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.
• Data Engineering
• 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.
• Data Performance & Optimization
• 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.
• Data Quality & Reconciliation
• 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.
• Data Analytics Enablement
• 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.

Required Qualifications

• 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.

Required Technical Skills

• 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

Preferred

• 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

Preferred 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.

What Success Looks Like

• Reliable, scalable, and well-governed data platforms.
• Tausted reporting supported by strong data quality and reconciliation processes.
• High-performance analytical environments that scale with business growth.
• Reduced operational overhead through automation and platform improvements.
• Data architectures that enable future analytics and AI initiatives.
• Strong collaboration with engineering, product, and business teams to drive measurable business outcomes.

Additional Information

Job Type: Full-time, Exempt, Remote primarily East Coast time zone, Some Travel Required

Compensation: Competitive including paid time off, medical benefits, and the potential for an annual performance bonus, and/or equity

We foster a collaborative, engaging, mission-driven culture that values innovation and prioritizes customer success. We like to have fun together and support each other too!

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