Bloomberg
Senior Data Management Professional - Data Quality - Events and Transcripts
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Senior Data Management Professional - Data Quality - Events and Transcripts
Data Quality Engineer – Events & Transcripts
Location
London
Business Area
Ref #
10051901
About Bloomberg Data
Bloomberg runs on data. Our platforms rely on powerful information to provide clients with accurate, context-rich analytics globally, 24/7. The Data team powers these systems with innovative technology, improving workflows by solving real-world challenges to enhance products, processes, and customer experiences.
The Team
Our Events and Transcripts Data team is seeking a Data Quality Engineer to elevate our datasets for reliability, scalability, and client-demand accuracy. The team partners closely with Product, Engineering, Sales, and News to design actionable data solutions that underpin workflows globally.
To succeed here, you’ll need:
- Cross-functional collaboration across teams globally
- Domain expertise in event and transcript data
- Automation & governance mindset to streamline pipelines
- Client-driven problem-solving to meet evolving needs
About the Role
You’ll own data quality strategy for Events and Transcripts, ensuring datasets meet ** accuracy, completeness, and usability** standards for critical client use cases. Key responsibilities include:
Key Responsibilities
- Design and implement data quality frameworks, aligning them with client needs and industry standards
- Define, measure, and monitor quality KPIs, ensuring traceability across workflows
- Oversee data ingestion and system integration, improving private markets scalability
- Collaborate with Eng, Product, and Data teams to embed quality-by-design principles
- Address data quality issues via profiling, statistical analysis, and root-cause investigations
- Build visualization dashboards (using Bloomberg tools like Business Rule Engines and QlikSense) to track accuracy, timeliness, and completeness
- Balance technical expertise with product innovation to meet client requirements
- Lead quarterly data quality reporting and governance documentation
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You’ll Trust Yourself To
✔ Develop and scale the data quality strategy for Events & Transcripts ✔ Define data quality metrics with transparency in reporting ✔ Govern data pipelines—new and existing—to enhance interoperability ✔ Drive methodology adoption, advocating for data quality best practices ✔ Partner with Product, Engineering, and Data teams on pipeline improvements ✔ Translate insights into actionable problem-solving for complex datasets ✔ Develop business rules + visual metrics for real-time accuracy checks
Skills and Experience
Essential
- Bachelor’s degree or higher in Computer Science, Mathematics, or Data Technology (or equivalent professional experience)
- Demonstrated career growth (proactive learning, role progression)
- 3+ years in data quality, governance, or data science
- Proficiency in Python, SQL (relational/NoSQL), and ETL pipelines
- Engineering experience with Tech Stacks (Amazon S3, Lambda, Kafka, Apache Airflow, or Bloomberg tech stack)
- Strong problem-solving: statistical rigor + logical methodology
- Collaborator extraordinaire—adaptable in distributed teams
- Technical + non-technical communication: Influence stakeholders, clarify complex findings
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Nice to Have (If It Sounds Like You!)
✅ Data Management Association certifications (CDMP, D&O, DCAM) ✅ Fluency in numerical analysis + A/B testing of data-derived solutions
This Seems Like a Pretty Sweet Fit
Apply if… ✔ You thrive at the intersection of data+technology+product ✔ Your career reflects ownership of complex systems ✔ You can intelligently critique quality in real-time, or drastically improve it
Note: Yes, years of experience are guidance—not absolute requirements. If the skills align, let’s talk!
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