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Senior Staff Data Engineer

Intuit

$185,500 - $275,500
Oct 24, 2025
Plano, TX, US
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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. This role is central to 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.