Assistant Director - Marketing Data Engineer
Listed on 2026-03-15
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IT/Tech
Data Analyst, Data Science Manager, Data Engineer
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it.
We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
Skills and CompetenciesProven experience owning end-to-end data transformation and modelling to produce trusted, analytics-ready datasets for business teams
Strong understanding of layered data architecture patterns (e.g. medallionstyle approaches), including clear separation between raw ingestion, transformation, and analyticsready consumption layers
Strong hands-on capability building and maintaining data models in Snowflake and implementing dbt transformation patterns at scale
Deep SQL expertise with strong data modelling skills including dimensional modelling and metrics definitions for consistent reporting
Demonstrated experience establishing a governed semantic layer for Power BI to reduce downstream modelling complexity and improve consistency
Ability to design and maintain reusable, documented data products that reduce single points of dependency and enable wider self-service reporting
Strong understanding of marketing data domains and KPIs, including how campaign, lifecycle, and engagement data should be structured for reporting and analytics
Experience designing and maintaining robust join strategies and identifier frameworks to link marketing, engagement, and commercial data across platforms
Design data models that support diagnostic analysis, enabling teams to understand drivers of performance changes, not just outcomes.
Working knowledge of data governance concepts including documentation, version control, testing, and change management to support long-term maintainability
Awareness of data privacy and consent considerations in marketing datasets with a commitment to responsible and secure handling of customer and contact data
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Marketing Analytics, or a related discipline preferred
Own upstream marketing data transformation and modelling to scale reports and dashboards today and enable AI-ready analytics tomorrow
Own Snowflake-based marketing data transformations and implement dbt models to generate clean, well-structured datasets for reporting and analytics
Reduce dependency on bespoke Business Intelligence-layer models by shifting business logic and modelling upstream into Snowflake
Improve resilience and continuity by eliminating single points of dependency through robust documentation, shared ownership, and repeatable patterns
Partner with Business Intelligence resources to separate responsibilities clearly so dashboard specialists can focus on front-end delivery and insights
Define and maintain marketing KPI logic and data definitions so reporting and dashboard outputs remain consistent across use cases and teams
Implement testing, version control, and change management practices for marketing data models to improve quality, traceability, and maintainability
Troubleshoot data issues and resolve modelling defects that impact dashboards, reporting, and downstream consumers
Collaborate with central data teams to align standards, ensure platform compatibility, and support broader analytics initiatives
Enable knowledge transfer and upskilling within the team through shared documentation,…
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