Marketing Data Engineer

• →Design, develop, and maintain automated data pipelines and workflows using Alteryx, Google Cloud Platform, SQL, and Python.
• →Build, maintain, and troubleshoot API integrations with digital marketing and advertising platforms to support reliable data ingestion.
• →Own the full lifecycle of assigned data pipelines, including design, data preparation, coding, testing, deployment, monitoring, optimization, and support.
• →Monitor pipelines proactively and resolve data inconsistencies, gaps, and processing errors before they affect reporting or analysis.
• →Collect, cleanse, validate, transform, and document marketing data from multiple sources.
• →Develop and maintain data models, databases, and reusable datasets that support analytics, reporting, and self-service analysis.
• →Partner with analysts and stakeholders to gather business and technical requirements and translate them into scalable data solutions.
• →Ensure data structures support accurate measurement of key marketing metrics, including ROAS, CPA, CTR, reach, engagement, conversion rate, and attribution.
• →Support dashboard and reporting environments by ensuring underlying data is complete, accurate, and timely.
• →Maintain technical documentation for pipelines, integrations, data definitions, and processes to support knowledge sharing and business continuity.
• →Develop automation solutions and implement improvements that increase the speed, reliability, scalability, and maintainability of data operations.
• →Apply AI and large language model (LLM) tools to enhance data engineering workflows, including data cleansing, anomaly detection, documentation, and code generation.

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