Data Quality Analyst

Capgemini; Dubai; On-site; AED 120,000 - 200,000; Full time

Job summary

A global consulting leader in Dubai seeks a Senior Data Quality Analyst to design and implement data quality frameworks. Candidates should have deep experience with Python, data governance tools like Collibra, and work in Azure Databricks. The role emphasizes collaboration, continuous improvement, and mentoring, with competitive benefits and career growth opportunities.

Benefits

Competitive remuneration

Professional certification support

Access to global learning platforms

Qualifications

• 5+ years of progressive experience in data quality engineering.
• Expertise in developing reusable data quality and validation libraries.
• Strong analytical and problem-solving skills.

Responsibilities

• Design and implement automated data quality checks using Python and Collibra.
• Define and enforce data quality metrics and Service Level Agreements.
• Act as a Level 2/3 escalation point for data quality incidents.

Skills

Python

Collibra

Data Governance

Agile Methodologies

Azure Databricks

Education

Bachelor's or Master’s degree in Computer Science, Data Management, Information Systems

Tools

ETL/ELT

Python Libraries

Data Visualization Tools

Job description

Senior Data Quality Analyst – Capgemini

About Capgemini

Capgemini is a global leader in consulting, digital transformation, technology, and engineering services. With a presence in over 50 countries and a strong heritage of innovation, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Our collaborative approach and a people-centric work culture have made us a partner of choice for clients across industries.

Role Overview

We are seeking a highly skilled Senior Data Quality Analyst with a robust background in designing, implementing, and maintaining data quality frameworks leveraging Python or Collibra. The ideal candidate will be adept at ensuring data accuracy, consistency, completeness, and reliability across large-scale cloud-based platforms, especially within Azure Databricks environments. This role requires expertise in automated data quality assurance, a deep understanding of data governance, and hands-on experience integrating quality controls into modern data pipelines.

The Senior Data Quality Analyst will be embedded within an agile squad dedicated to a specific business mission while contributing to a broader program comprising 4 to 8 interconnected squads. Collaboration, technical leadership, and a continuous improvement mindset are essential as you work cross-functionally to elevate the organization’s data quality standards.

Key Responsibilities

1. Development & Integration

• Design, develop, and implement automated data quality checks using Python scripts and libraries or Collibra Data Quality components.
• Integrate data quality validation logic within existing ETL/ELT pipelines operating on Azure Databricks, ensuring quality gates are consistently enforced across all data flows.
• Develop and maintain reusable Python modules that perform anomaly detection, schema validation, and rule-based data quality checks to enable rapid scaling of quality coverage.
• Collaborate with data engineering teams to embed continuous quality controls throughout the data ingestion, transformation, and consumption lifecycle.
• Support the deployment and management of Collibra-based data quality solutions to automate governance workflows and stewardship activities.

2. Data Quality Management

• Define, measure, and rigorously enforce data quality metrics, thresholds, and Service Level Agreements (SLAs) tailored to business-critical datasets.
• Utilize Collibra to manage and operationalize data governance workflows, maintain business glossaries, and delineate stewardship responsibilities.
• Monitor the integrity of data pipelines for completeness, accuracy, timeliness, and consistency across distributed and cloud-native environments.
• Conduct detailed root cause analyses for complex data quality issues, collaborating with engineers and domain experts to drive permanent remediation and prevention strategies.
• Implement and continuously refine monitoring frameworks, utilizing dashboards and alerting systems (built using Python and Collibra integrations) for real-time visibility into key data quality indicators.

3. Support & Operations

• Act as a Level 2/3 escalation point for data quality incidents, troubleshooting issues and coordinating with other agile squads and technical teams for rapid resolution.
• Work closely with product owners, business analysts, and key stakeholders to understand evolving data requirements and ensure quality expectations are aligned and met.
• Maintain and optimize operational dashboards for ongoing data quality monitoring, leveraging both Python-based and Collibra-integrated solutions.
• Participate actively in agile ceremonies, including sprint planning, daily standups, reviews, and retrospectives, contributing to squad goals and continuous delivery improvements.

4. Governance & Best Practices

• Establish, document, and evangelize data quality standards, validation frameworks, and best practices across squads and the broader data organization.
• Maintain comprehensive documentation on validation rules, automated test cases, and quality assurance procedures, ensuring transparency and repeatability.
• Mentor, coach, and upskill junior data engineers and analysts in data quality concepts, tools, and processes to foster a quality-first culture.
• Ensure strict compliance with data governance, privacy, and security policies by leveraging Collibra’s governance and stewardship frameworks.
• Continuously assess emerging technologies, tools, and methodologies for potential enhancement of the data quality ecosystem.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Management, Information Systems, or a closely related field.
• Years of progressive experience in data quality engineering, data management, or related data roles within complex technology environments.
• Demonstrable expertise in Python, including the development of reusable data quality and validation libraries.
• Extensive hands-on experience with Azure Databricks, including cloud-native data processing, ETL/ELT orchestration, and distributed computing concepts.
• Proficiency with Collibra Data Quality platform or equivalent data governance and stewardship tools.
• Strong track record working in agile environments, participating in cross-functional teams, and adapting to rapidly evolving project requirements.
• Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical topics to both technical and non-technical audiences.

Preferred Certifications (One or More)

• Databricks Certified Data Engineer Associate or Professional
• Microsoft Certified: Azure Data Engineer Associate
• Python Institute Certifications (PCAP, PCPP)
• Collibra Ranger or Collibra Data Quality Steward Certifications

Key Skills & Competencies

• Deep understanding of data quality frameworks, methodologies, and industry best practices
• Hands-on experience building automated data quality tests using Python, PySpark, or similar open-source libraries
• Expertise in designing quality validation steps within ETL/ELT data pipelines for large volumes of structured and semi-structured data
• Familiarity with cloud data ecosystems, especially Azure and Databricks
• Proven ability to operationalize and scale data governance using Collibra or comparable tools
• Experience with dashboarding, data visualization, and monitoring tools for real-time data quality tracking
• Strong collaboration, leadership, and mentoring abilities within agile squads or matrix teams
• Knowledge of data privacy, security, and regulatory compliance requirements
• Ability to drive innovation and continuous improvement in data quality processes

What We Offer

• Opportunity to work on cutting-edge data platforms and technologies in a global, multicultural environment
• Collaborative and agile work culture with empowering career growth opportunities
• Competitive remuneration, benefits, and professional certification support
• Access to Capgemini’s global learning platforms, mentorship programs, and technology communities
• Exposure to high-impact projects with Fortune 500 clients