- Information Technology
- India - Bangalore Sales Office
The team are a multi-disciplinary, global team providing round-the-clock development and operations – including product and project management, community enablement, governance, data architecture, data engineering, data science, and analytics expertise.
Involved with every aspect of Dyson’s global business - from finance to product development, manufacturing to owner experience – data is enjoying record-breaking investment and mandate for 2021 and beyond, seeking to deliver solutions generating impressive and tangible business value.
Data and analytics excellence at Dyson are delivered by a diverse and collaborative global community spread across Dyson locations from UK to Chicago, Shanghai to Singapore. Domain-specific experts form spoke analytics teams, enabled by a central team at the hub. All teams benefit from significant recent investments in cloud technologies and tools, combined with an expansive scope and no shortage of ambition and momentum; data and analytics are recognized throughout the organization, to the highest level, as critical to all of Dyson’s strategic objectives.
As the ‘hub’ team delivering the data, technology and community provision enabling Dyson’s global data and analytics capabilities, Global Data Function (GDF) have end-to-end responsibility for data from foundations (DQ, MDM) to management (data platforms, integrations), to value realization (analytics enablement and delivery).
About The Role:
We are seeking a highly skilled Principal Data Quality Engineer to lead our Quality as Code initiative. The successful candidate will be responsible for developing and implementing quality processes and tools for our data management teams. They will work closely with cross-functional teams to ensure quality is embedded throughout the data lifecycle. The Principal Data Quality Engineer will be responsible for leading and mentoring a team of Data Quality Engineers, providing guidance on best practices, and driving continuous improvement.
- Develop and implement quality processes and tools for our data management teams
- Collaborate with cross-functional teams to ensure quality is embedded throughout the data lifecycle
- Lead and mentor a team of Data Quality Engineers, providing guidance on best practices and driving continuous improvement
- Develop and maintain automated testing frameworks for data quality testing, including data profiling, data validation, and data reconciliation
- Ensure code quality by implementing code review and static analysis tools for data pipelines and workflows
- Develop and maintain continuous integration and delivery pipelines to support automated testing and deployment of data pipelines and workflows
- Develop and maintain documentation for quality processes and procedures
- Monitor and analyze quality metrics to identify trends and areas for improvement
- Partner with data management teams to identify quality issues and develop solutions
- Drive the adoption of quality as code tools and technologies for data management
- Participate in quality audits and compliance reviews
- Bachelor's or Master's degree in Computer Science, Information Systems, or related field
- 10+ years of experience in data quality management or related field
- Experience leading and mentoring a team of Data Quality Engineers
- Strong experience in quality as code practices and tools for data management, such as Apache NiFi, Apache Beam, Apache Kafka, Apache Airflow, etc.
- Strong analytical and problem-solving skills • Excellent communication and collaboration skills
- Proficient in at least one programming language such as Java, Python, Scala, etc.
- Knowledge of agile data management methodologies
- Experience with cloud-based platforms such as AWS, Azure, or GCP is a plus
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.