Data Engineer Client Data Operations

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer Client Data Operations based in the United States . The Data Engineer will play a key role in building, maintaining, and optimizing the data infrastructure that supports client marketing campaigns, audience management, and business reporting. This hands-on position focuses on onboarding new client data, transforming complex and inconsistent source files into reliable production-ready datasets, and ensuring data pipelines operate efficiently. You will take ownership of production workflows, troubleshoot technical issues, and develop scalable ingestion processes using modern cloud technologies. Working closely with analytics, campaign, account, and technical teams, you will help ensure data accuracy, security, and seamless campaign delivery. This is an individual contributor role offering significant autonomy and the opportunity to improve operational processes within a growing, data-driven environment. The position is fully remote across the United States, with a preference for candidates located in the Dallas, Texas area. Accountabilities: - Client Data Onboarding: Set up and manage incoming data feeds from client and vendor systems, including SFTP connections and scheduled file deliveries. Analyze source files, identify missing fields, inconsistent formats, and schema changes, and map incoming information into established database structures. - Data Validation and Processing: Develop validation, identity matching, and data preparation processes, including record-count reconciliation, LTID assignment, and CASS/NCOA processing when applicable. Ensure data quality before it enters production workflows. - Pipeline Development: Build, maintain, and optimize scalable data pipelines using SQL, Python, and Spark to support new direct mail and digital marketing clients.

Establish reusable data structures and avoid unnecessary one-off solutions. - Workflow Automation: Configure scheduled jobs, file monitoring, transformations, testing, and automated alerts to minimize manual intervention and improve pipeline reliability. - Production Monitoring and Troubleshooting: Own daily monitoring and maintenance of Databricks workflows, AWS jobs, and related data tools. Investigate and resolve pipeline failures, schema changes, expired credentials, broken dependencies, stale data, and vendor-related issues. - Campaign and Mail Production: Manage routine audience and direct mail production activities, including data suppression, address hygiene, record reconciliation, quality control, and preparation of files for external vendors, following established approval procedures. - Operational Documentation: Create and maintain clear documentation covering data sources, transformations, validation processes, outputs, troubleshooting procedures, and recovery workflows. - Data Security and Compliance: Identify sensitive information and apply approved privacy, access, and data-handling policies. Escalate ambiguous data governance or privacy questions to the appropriate stakeholders. - Cross-Functional Collaboration: Work closely with the Senior Analytics Engineer to provide clean, consistent, well-documented datasets for downstream modeling, analysis, and reporting. - Stakeholder Communication: Collaborate with campaign, account management, and technical teams to clarify requirements, resolve data issues, communicate delivery risks, and recommend appropriate solutions. - Continuous Improvement: Identify opportunities to strengthen pipeline monitoring, automate recurring tasks, improve operational efficiency, and reduce dependency on manual troubleshooting. Requirements: - Several years of hands-on data engineering experience, ideally 4+ years , including building, maintaining, and operating production data pipelines.