Limetree

Data Engineer

• Set up new feeds from client and vendor systems, including SFTP and scheduled file deliveries
• Identify source fields, changes, missing data, and inconsistent formats
• Map incoming data into established schemas and tables, identify sensitive fields, and apply approved privacy and access rules
• Build validation and matching steps, including record counts, identity matching or LTID assignment, and CASS/NCOA processing where relevant
• Document feed inputs, transformations, checks, outputs, and failure procedures
• Build and extend SQL, Python, and Spark pipelines for direct mail and digital clients
• Set up scheduled jobs, file watchers, transformations, testing, and monitoring
• Improve existing pipelines as source files, schemas, tools, and business requirements change
• Perform daily checks and troubleshoot Databricks workflows, AWS jobs, and related tools
• Investigate failures and fix root causes, including schema drift, bad source files, expired credentials, broken dependencies, stale data, and vendor-tool issues
• Improve alerts, recovery steps, and runbooks
• Own routine audience and mail-drop production, including suppressions, address hygiene, count reconciliation, QC, and vendor file preparation
• Flag risks to scheduled client drops and recommend safe resolutions
• Hand off reliable, documented data to the Senior Analytics Engineer for downstream modeling, analysis, and reporting
• Partner with campaign, account, and technical colleagues to clarify requirements and resolve issues

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Data Engineer – Client Data Operations