Intuit's Marketing Operations team needs to transition its marketing data onboarding process for TY'25 and beyond by implementing and managing a modern data architecture that enhances data integrity and operational efficiency. The MOPS Data Engineer will be central to this strategic transition, ensuring seamless data flow and quality for high-impact marketing activations.
Requirements
- Proficient to expert-level skills in data engineering, with a strong background in ETL processes and data pipeline development.
- Proficiency in scripting languages, specifically Python and JavaScript.
- Expertise in SQL for writing complex queries, performing joins, and data profiling.
- Familiarity with data models, data structures, and schema management.
- Understanding of both streaming (e.g., Kafka) and batch data processing constructs.
- Experience with modern ETL platforms; direct experience with SnapLogic is highly desirable.
- Experience with MarTech platforms like Adobe Experience Platform (AEP) is a strong plus.
Responsibilities
- Design, build, and maintain scalable data pipelines using SnapLogic, our new modern ETL platform.
- Manage the flow of data from our Change Data Capture (CDC) system into the new Marketing Data Warehouse (MDW), including integrations, data mapping, and transformation logic.
- Strictly adhere to transformation guardrails within SnapLogic, permitting only marketing-specific transformations (e.g., scalar operations, simple IF/ELSE conditional logic, string and number manipulations, date masking/formatting), and prohibiting API calls or hard-coded filters.
- Test and validate ETL pipelines, ensuring data accuracy and reliability for marketing activation.
- Adhere to SDLC best practices, including peer reviews, version control, and deployment processes for all production implementations.
- Troubleshoot and debug complex issues within data pipelines.
- Configure and manage CDC to MDW Parity Checks to validate CG (Customer Group) data for count and value consistency between the source (CDC) and the Marketing Data Warehouse (MDW).
Other
- Ability to work effectively in a fast-paced, collaborative, and innovative environment, understanding organizational dynamics and decision pathways.
- Strong critical thinking and problem-solving skills, coupled with a curious mindset.
- Awareness of key business data elements, SLAs, and regulatory requirements relevant to marketing data.
- Ensure solid understanding and adherence to data security, privacy, and PII handling best practices.
- Act as a trusted bridge between data engineering, platform, and business teams, translating complex business requirements into resilient, observable pipeline flows.
