You will be responsible for building and evolving the frameworks that ensure trust, reliability, and accuracy across our modern data platform. Working closely with Analytics Engineers, Data Engineers, and Data Analysts, you will design intelligent data quality, testing, monitoring, and alerting frameworks that protect critical business processes and KPIs while enabling scalable and reliable data products.
What You'll Do:
- Design, implement, and continuously improve data quality frameworks across the data platform.
- Build and maintain automated data quality tests, validation controls, monitoring frameworks, and source freshness checks throughout the data lifecycle.
- Establish quality standards and practices that can be consistently adopted across the organisation.
- Embed data quality controls throughout the data development lifecycle to improve reliability before issues reach production. Develop Intelligent Testing, Monitoring & Anomaly Detection
- Develop statistical checks and anomaly detection techniques to identify unexpected changes in data and business metrics.
- Design intelligent testing approaches that balance rigorous quality standards with pragmatic operational practices.
- Identify and distinguish between minor data inconsistencies and data quality incidents requiring immediate action.
- Continuously improve monitoring approaches to maximise data reliability while minimising unnecessary alerts and alert fatigue. Design Alerting & Incident Management Processes
- Design alerting and notification frameworks that prioritise data quality issues based on business impact.
- Establish incident management processes for responding to critical data quality issues.
- Investigate data quality incidents and perform end-to-end root cause analysis across ingestion, transformation, and reporting layers.
- Translate technical data quality issues into clear business impact and actionable improvements. Partner Across the Data & Analytics Organisation
- Work closely with Analytics Engineers, Data Engineers, Data Analysts, and other stakeholders to improve the quality and reliability of data products.
- Collaborate with cross-functional teams to understand business processes, KPIs, and the impact of data quality issues on business outcomes.
- Support teams in identifying quality risks across complex data pipelines and systems.
- Drive consistent adoption of data quality standards, automation, testing, and continuous validation practices. Enable Data Quality Visibility & Continuous Improvement
- Create and maintain reporting and dashboards that provide visibility into data quality health across the platform.
- Track and communicate test coverage, data quality incidents, alert volumes, and quality trends.
- Use data quality insights to identify recurring issues, improvement opportunities, and areas of operational risk.
- Guide and train teams on data quality frameworks, testing strategies, observability practices, and reliability standards.
What It Takes:
- 4+ years of experience in Analytics Engineering, Data Analytics, Data Quality, or a related data-focused role.
- Strong SQL skills and experience working with analytical datasets and data models.
- Strong analytical and statistical mindset, with the ability to identify patterns, anomalies, and data quality risks.
- Strong understanding of business processes, KPIs, and the impact of data quality issues on business outcomes.
- Experience designing and implementing data quality controls, monitoring frameworks, validation processes, and source freshness checks.
- Experience embedding automated testing, validation, and quality controls into CI/CD and development workflows.
- Experience performing root cause analysis across complex data pipelines and systems.
- Hands-on experience with dbt, SQLMesh, or similar SQL-based transformation tools.
- Experience working with modern data platforms and cloud data warehouses is preferred. Leadership & Collaboration
- Experience working closely with Analytics Engineers, Data Engineers, Data Analysts, and cross-functional stakeholders.
- Strong communication and stakeholder management skills, with the ability to translate technical data quality issues into business impact.
- Ability to influence teams and drive consistent adoption of data quality standards and best practices.
- Strong problem-solving skills with a structured and pragmatic approach to investigating data quality issues.
- Ability to balance technical quality requirements with operational priorities and business impact. Mindset
- Quality-focused mindset with a strong commitment to data reliability, accuracy, and trust.
- Pragmatic approach to problem solving, recognising that not every data issue carries the same level of business impact.
- Analytical and curious approach to identifying patterns, anomalies, and underlying causes.
- Continuous improvement mindset with a focus on automation, scalability, and operational excellence.
- Strong sense of ownership for the reliability and trustworthiness of data products.
- Collaborative mindset with a passion for enabling teams to adopt better data quality and reliability practices.
Skills Required
- 4+ years in Analytics Engineering, Data Analytics, Data Quality, or related data role
- Strong SQL skills working with analytical datasets and data models
- Hands-on experience with dbt, SQLMesh, or similar SQL-based transformation tools
- Designing and implementing data quality controls, monitoring frameworks, validation processes, and source freshness checks
- Embedding automated testing, validation, and quality controls into CI/CD and development workflows
- Experience performing root cause analysis across complex data pipelines and systems
- Strong analytical and statistical mindset for anomaly detection and pattern identification
- Experience working with modern data platforms and cloud data warehouses
- Strong communication, stakeholder management, and ability to translate technical issues into business impact
- Ability to design alerting, incident management processes, and drive adoption of data quality practices
Protolabs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Protolabs and has not been reviewed or approved by Protolabs.
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Healthcare Strength — Medical, dental, and vision options are broadly available and described as good to excellent. Additional protections like short- and long-term disability and life insurance bolster the overall package.
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Leave & Time Off Breadth — A starting PTO allotment plus paid holidays, along with added wellness and volunteer time, is emphasized, with some roles noting PTO growth over tenure. Paid caregiver leave appears in postings and supports flexibility for life events.
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Retirement Support — A 401(k) with company match and immediate vesting is offered, supporting long-term savings. This foundation is frequently cited alongside core financial benefits as a strong element of total rewards.
Protolabs Insights
What We Do
Protolabs is the world's fastest digital manufacturing source for rapid prototyping and on-demand production. The technology-enabled company produces custom parts and assemblies in as fast as 1 day with automated 3D printing, CNC machining, sheet metal fabrication, and injection molding processes. Our digital approach to manufacturing enables accelerated time to market, reduces development and production costs, and minimizes risk throughout the product life cycle. 3D Printing Our 3D printing service offers a wide selection of materials and technologies to create prototypes and end-use parts with complex geometries and detailed features. With tight process controls, careful design reviews, and extensive quality monitoring, we ensure precise and repeatable 3D-printed parts, every time. CNC Machining We use 3- and 5-axis milling along with turning to machine parts from commercial-grade plastics and metals. Our online quoting system and automated manufacturing process enable us to ship parts within 24 hours, helping customers accelerate development and reduce time to market. Sheet Metal Fabrication Protolabs is an industry leader in quick-turn sheet metal parts for both prototyping and low-volume production. Our digital approach to manufacturing enables us to fabricate sheet metal parts in as fast as 5 days. Additionally, we can support our customers’ development efforts with component assemblies, several finish options, and screen printing. Injection Molding Our injection molding service offers two options—prototyping and on-demand manufacturing—which provide customers a tooling solution that aligns with their project’s requirements. It’s used for quick-turn prototyping, bridge tooling, and low-volume production of up to 10,000+ parts in 15 days or less.
