Senior Software Engineer - Data Governance & Management Platforms
About The Position
Bloomberg’s Data Services team, within the Data Management & Analytics Engineering department, builds platforms, services, and data products that help the firm understand, govern, protect, improve, and use data at scale. The team’s capabilities include data discovery, cataloging, classification, lineage, data quality, observability, reference and enrichment services, master data, common data, and usage data, with cross-cutting responsibilities across stewardship, metadata, semantics, privacy, controls, and architecture standards. The role is described as a technical lead and architect for the future-state Data Services platform, bridging data management requirements with high-performance software engineering. It involves driving architecture, setting standards, building prototypes, and guiding engineering teams across the department, while also contributing hands-on code and system design.
Requirements
- Deep proficiency in software architecture and problem-solving, with proven hands-on coding capabilities in languages such as Python, C++, Java, Scala, or Go.
- At least 7 years of industry experience in software engineering, data management, data governance, metadata platforms, or enterprise data architecture.
- Comprehensive understanding of data cataloging, metadata management, lineage tracking, data quality frameworks, observability, stewardship, and semantic layers.
- Demonstrated success architecting distributed systems, data pipelines, metadata integration workflows, and API-driven data platforms.
- Exposure to or experience implementing mature enterprise data platforms such as DataHub, OpenMetadata, Collibra, Alation, Atlan, or Purview, or custom internal equivalents.
- Proven ability to lead architectural discussions, communicate complex technical topics to diverse stakeholders, and mentor engineering teams.
Nice To Haves
- Experience with semantic technologies, knowledge graphs, ontologies, and master/reference data management.
- Familiarity with AI/ML-driven data governance automation, such as automated data classification, anomaly detection, metadata enrichment, or automated lineage inference.
- Background serving as a Manager, Tech Lead, Platform Architect, or Principal SME in an enterprise-scale data ecosystem.
Responsibilities
- Define future-state architecture patterns and engineering standards for metadata capture, lineage, data quality, observability, data contracts, and semantic modeling.
- Transform data governance and management capabilities into production-ready software patterns, reusable APIs, metadata flows, and platform workflows.
- Write clean, optimized code; build prototypes; bootstrap critical modules; and validate technical implementations to de-risk complex platform updates.
- Partner across Data Governance Services, Data Integrity Services, Common Data Products, and Usage Data Products to connect services into a cohesive platform.
- Collaborate with engineering leads, product managers, data stewards, and data engineers to reduce duplication, enforce standards, and improve engineering quality.
- Evaluate modern enterprise data management tools and trends, assess build-versus-buy choices, and apply proven patterns from mature data organizations.
- Lead architectural discussions, communicate technical topics to diverse stakeholders, and mentor engineering teams.
Benefits
- Merit increases
- Incentive compensation (exempt roles only)
- Paid holidays
- Paid time off
- Medical benefits
- Dental insurance
- Vision insurance
- Short- and long-term disability benefits
- 401(k) with company match
- Life insurance
- Wellness programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
