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Protocol Intelligence
Data-driven signals on your job's competitivenessEntry-level data engineering with common skills at a known financial employer yields moderate competition.
Core data engineering skills transferable across industries despite marketing-data context.
Requires specific data stack skills (Python, SQL, Snowflake) though no years mandated, so moderate strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Build, maintain, and optimize data pipelines supporting marketing analytics, campaign measurement, brand tracking, and customer segmentation.
Process and deliver large-scale marketing and customer data ensuring accuracy, completeness, and timeliness for end-users.
Implement automated data quality controls, resolve systemic data errors, manage production releases, and support data governance aligned with enterprise strategy.
Minimum Requirements
Strong hands-on experience with Python and SQL for data extraction, transformation, and validation.
Experience with Snowflake or similar cloud-based data platforms (e.g., AWS).
Understanding of data quality concepts, API/File Transfer-based pipelines, and ETL/ELT processes.
Work Experience Required: No Experience Required
Ideal Candidate Profile
Comfortable working under direct supervision on complex, large-scale marketing data engineering projects involving multiple stakeholders.
Capable of collaborating across marketing technology, analytics, and business teams to translate data requirements into scalable engineering solutions.
Familiarity with marketing data platforms (Google Analytics, SFMC, CRM) and awareness of data governance and responsible AI concepts preferred but not mandatory.