Data Engineer responsible for developing research analytic data infrastructure at Sutter Health. Involves managing data quality, pipelines, and compliance with healthcare regulations.
About the role
- Data Engineer at StarRez designing and maintaining data pipelines for analytics. Collaborating with teams to drive data quality and insights across the product.
Responsibilities
- Build and maintain scalable data pipelines to ingest, transform, and model data for analytics and reporting
- Develop and optimise data models to support consistent dashboards and KPI definitions
- Ensure data quality and reliability through testing, monitoring, and observability practices
- Work with Data Analysts and Product teams to translate requirements into reusable datasets and pipelines
- Collaborate with Engineering to support data integration, schema automation, and platform scalability
- Integrate data from internal and external sources (APIs, third-party systems)
- Improve performance, scalability, and cost efficiency of the data platform
- Contribute to embedding analytics into the product (dashboards, reporting, data services)
- Support advanced use cases such as forecasting, benchmarking, and data-driven insights
Requirements
- Experience designing and maintaining ETL/ELT pipelines (batch and/or streaming)
- Experience with cloud data platforms (e.g., Snowflake, Azure Synapse, Microsoft Fabric or similar) including IAC
- Familiarity with modern data tooling (e.g., dbt, Airflow, Fivetran, Azure Data Factory or equivalents)
- Understanding of data integration patterns (APIs, ingestion pipelines, transformation layers) and Solid understanding of data modelling (star schema, dimensional modelling, data warehousing concepts)
- Knowledge of data quality, testing, and observability practices (monitoring, validation, lineage)
- Strong database fundamentals and SQL experience; comfortable designing safe schema changes considering performance optimisation, scalability, and cost management in data systems
- Ability to work closely with Data Analysts and stakeholders to translate requirements into scalable data solutions
- Strong communication skills with the ability to turn ambiguous requirements into structured data models and pipelines
- Pragmatic approach to balancing speed, quality, and scalability
- An inclination towards communication, inclusion, and visibility
Benefits
- A Culture That Lasts: Many of our team members have been with us for 20+ years—a testament to our people-first philosophy.
- Global Impact, Local Ownership: Join a team that spans across Australia, the USA, the UK, and Canada, working on industry-leading solutions, while building the centre up from ground up.
- Long-Term Vision: We’re not here for short-term gains. We invest in our people for the long haul, creating an environment where you can grow, lead, and thrive.
- Innovation with Stability: Backed by Vista Equity Partners, we combine the agility of a scaling SaaS company with the stability of long-term industry leadership.
- Z-Factor: We take pride in our culture of passion, care, and high performance. The Z-Factor defines how we support our teams, foster growth, and ensure that everyone at StarRez thrives.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Senior Data Engineer designing impactful data solutions for clients at Simple Machines. Collaborating with engineers to build data platforms and pipelines in a hybrid workplace.
Journeyman Data Engineer at Leidos supporting DoD enterprise data and analytics. Develop and maintain data pipelines and data models with a focus on national security outcomes.
Senior Data Engineer at Corient designing and maintaining data pipelines for wealth management. Overseeing sprint planning and supporting cross - functional data initiatives to ensure data integrity.
Data Engineer responsible for designing and implementing data pipelines at United Community. Collaborating across teams to support data warehouse and maintenance of data products.
Data Engineer designing and building production data pipelines for AI and ML workloads at Capgemini Engineering. Focus on end to end data lifecycle management and AWS infrastructure.
Data Engineer designing and implementing scalable data architecture for HR and people analytics. Collaborating with teams to ensure reliable data pipelines and integration using modern technologies.
Senior Data Engineer architecting and maintaining scalable data systems while collaborating with cross - functional teams at SpotOn, aimed at empowering independent restaurants.
Analytics & Data Engineer joining a data - driven team at Adlook, building data products and automating data pipelines. Collaborate across teams to enhance data analysis and AI functionality.
Data Engineer building data foundations for People Analytics at Notion. Designing data systems and collaborating with People leadership to enhance workforce decision - making.