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Global brand, metro location, generalist engineer title, and broad data skillset increase candidate competition.
Core data engineering skills are transferable, though domain-specific sales/marketing warehousing knowledge increases fit sensitivity.
Specific mandatory tools (Snowflake, DBT, strong SQL) increase filtering despite no explicit years requirement.
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Design, build, and maintain robust data pipelines and analytical solutions supporting global sales and marketing teams.
Collaborate cross-functionally with product owners, database architects, and data analysts to translate requirements into scalable technical solutions.
Ensure reliability, performance, and business impact of data solutions while elevating team engineering quality.
Solid experience in data warehousing with hands-on expertise in Snowflake and DBT.
Strong SQL skills and experience with database modelling and design.
Experience with agile development tools such as Jira and Confluence, and CI/CD practices (preferably Jenkins or equivalent).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building and maintaining scalable data warehouses supporting sales and marketing analytics.
Capable of working with large, complex datasets and comfortable resolving performance and quality issues.
Familiar with emerging technologies such as AI and LLMs, with a continuous improvement mindset.