Assistant Director - Marketing 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 Competencies

• Proven 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. medallion‑style approaches), including clear separation between raw ingestion, transformation, and analytics‑ready 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

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Marketing Analytics, or a related discipline preferred

Responsibilities

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, repeatable processes, and targeted enablement support

• Create analytics-ready tables that enable thin, governed Power BI semantic models, promoting consistent metrics and scalable dashboard delivery across stakeholders

• Design and maintain a layered marketing data architecture that supports scalable reporting, governance, and future diagnostic/predictive use cases

• Demonstrated understanding of AI concepts with hands‑on experience building the data foundations that enable scalable, AI‑ready use-cases

• Proven ability to design governed, high‑quality data pipelines and models that support downstream AI and advanced analytics use cases

• Strong awareness of data governance, privacy, and AI risk considerations, enabling responsible and ethical AI adoption

About the team

Our Marketing Data Operations team is responsible for advancing how marketing performance is measured, understood, and utilized across the organization. We build trusted, outcome‑focused data products that power confident decision‑making today, while creating the platform for more advanced diagnostics and predictive insight as our analytics maturity grows.

As a Data Engineer, you will play a critical role in shaping the upstream data layer that underpins Marketing’s most important performance conversations and future insight capabilities.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.