Senior Data Engineer (Data Architecture)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Data Architecture) based in the United States. The Senior Data Engineer will help design, build, and evolve the data infrastructure powering a proprietary technology platform. You will work at the intersection of data engineering, architecture, product development, and client solutions to create reliable and scalable data capabilities. A significant portion of the role will focus on shared data products and platform architecture, while also supporting individual client pipelines. You will identify recurring needs across implementations and transform them into reusable models, frameworks, and configuration-driven solutions. The role places strong emphasis on data quality, testing, observability, standardization, performance, and long-term maintainability. You will collaborate with technical and business stakeholders while contributing to architecture decisions and mentoring other engineers. This is an opportunity to influence how modern data solutions are designed and scaled in a fast-moving, multi-client environment. Design, build, deploy, and maintain scalable data pipelines and shared data products using BigQuery, dbt, Python, and orchestration technologies. Translate business and client requirements into reliable, scalable, and maintainable technical solutions in partnership with Product, Engineering, and client-facing teams. Identify recurring patterns across client implementations and transform them into reusable models, frameworks, ingestion patterns, utilities, and shared capabilities. Develop configuration-driven solutions that balance standardization and scalability with the flexibility required by individual clients. Strengthen data reliability through automated testing, validation, reconciliation, monitoring, documentation, and observability practices. Improve existing data pipelines and architecture to increase scalability, maintainability, performance, and cost efficiency. Integrate, normalize, and process data from APIs and third-party platforms across the MarTech and AdTech ecosystem. Manage production data pipelines across a diverse client portfolio, troubleshoot complex issues, and identify systemic improvements that reduce recurring problems. Contribute to technical designs, architecture discussions, code reviews, engineering standards, and best practices. Provide technical guidance and mentorship to other Data Engineers while helping improve overall engineering effectiveness. Use AI-assisted development tools to accelerate coding, debugging, testing, documentation, code exploration, and reviews while maintaining accountability for production-quality output. Help evolve client-specific implementations into shared data products, frameworks, and vertical-focused capabilities, including Retail Media and B2B solutions. Requirements: Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience. 5+ years of experience in data engineering, analytics engineering, data architecture, or a related field. Demonstrated ability to independently design and deliver production-grade data pipelines and data models. Advanced SQL and BigQuery expertise, with strong knowledge of relational databases, analytical databases, data warehousing, and dimensional modeling. Intermediate to advanced Python programming skills. Strong hands-on experience with dbt, including data modeling, testing, documentation, and reusable development patterns. Proven experience improving or refactoring data systems for greater reliability, scalability, reusability, and maintainability. Familiarity with orchestration technologies such as Airflow, Dagster, AWS Glue, or Azure Data Factory. Experience with modern software engineering practices, including Git, code reviews, CI/CD, automated testing, and production support. Strong underst