Agent
Jobs
Applied
Tracker
Profile
    1. Jobs for you
    2. Job

    Job · 14995620

    HYDERABAD · FULLTIME

    Quality Engineer - Analytics

    Protolabs logo

    Protolabs

    Hyderabad · onsite · Posted 51d ago

    Sourced fromFoundit
    Not disclosed4–6 yrsfulltimeHyderabad

    About a minute. You'll make an account on the way through.

    agent · working

    • Read this posting0.8s
    • Found the form on Foundit · 13 questions to answer1.4s
    • Decided the answers for all of them2.5s
    • Tailor your résumé to this role
    • Waiting for you

    Section · 01

    About this role

    Join the team as our new Analytics Engineer (Quality) – India

    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

    Build & Evolve Data Quality Frameworks

    • 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

    Technical

    • 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.

    Sourced from foundit

    Section · 02

    Skills

    statistical checksautomated data quality testssource freshness checksdbtRoot Cause AnalysisSQLMeshData Quality FrameworksMonitoring frameworksanomaly detection techniquesincident management processesalerting frameworksSQL

    Section · Company

    About Protolabs

    Protolabs logo

    Protolabs

    Industrial Machinery

    7

    employees

    Maple Plain, MN

    US

    ₹12.6L PA avg

    Avg at Protolabs

    About

    Proto Labs is a digital manufacturing source for prototypes and low-volume production parts. Proto Labs specializes in digital manufacturing accelerating product development, reducing costs, and optimizing the supply chain. Their automated quoting and manufacturing systems allow them to produce commercial-grade plastic, metal, and liquid silicone rubber parts. Their services include injection molding, CNC machining, 3D printing, sheet metal fabrication, and more.

    Industries

    Industrial Machinery

    Employee ratings

    2 reviews

    4.5/ 5

    Culture

    4.5

    Career growth

    4.5

    Work-life

    5.0

    Employees rate it well for

    Job Security50Work-Life Balance50

    Find them on

    WebsiteLinkedInAmbitionBox reviews

    Quality Engineer - Analytics · waiting for your command