Senior Data Engineer

About the Team & the Role The Core Data team builds and scales a best-in-class data platform and analytics capabilities that power decision making across client. Within Core Data, the Operational Insights team focuses on production environments: we turn rich operational and quality signals into trusted data products and metrics that help improve business processes and performance. Title Senior Data Engineer Location Palo Alto, CA Working Hours 8am-5pm Duration 4 Months Experience Expected 7-15 Years Job Description As a Sr. Data Engineer, you will help build and operate the data foundation that powers analytics across programs and sites. You will design and maintain scalable ingestion pipelines, develop well‑modeled datasets, and ensure data quality and reliability across critical systems. This role sits at the intersection of operational systems, modern data platform engineering, and analytics enablement, helping convert raw operational signals into governed, high‑value datasets that power analytics applications, core metrics, and future AI‑driven insights. What You Will Do Design, build, and operate data ingestion pipelines from operational, quality, test, and service systems into Databricks using Fivetran/AWS/Databricks and standardized ELT patterns. Develop and maintain dbt models for operational, quality, and ramp metrics, following our standard patterns for analytics. Set up and maintain data quality checks, audits, and monitoring for freshness, completeness, and contract compliance across key pipelines. Optimize Databricks jobs, Fivetran connectors, and dbt runs for performance, cost, and reliability, including orchestration, alerting, and runbooks. Collaborate with analytics engineers and product teams to turn models into high‑value data products powering analytics applications. Contribute to the semantic layer and catalog so GenAI agents and self‑service tools can reliably discover and query operational data. Drive improvements in upstream systems and schemas to reduce data issues at the source. Qualifications Required 6+ years of experience in Data Engineering, Analytics Engineering, or Software Engineering working with production data systems. Strong expertise in SQL and Python for building scalable data pipelines and transformations. Hands‑on experience building ELT pipelines using modern cloud data platforms (Databricks strongly preferred). Deep experience with dbt, including model development, testing, documentation, and CI/CD integration. Experience with managed ingestion tools such as Fivetran, Airbyte, or similar. Experience designing and operating production‑grade data pipelines with monitoring and observability. Strong collaboration skills and ability to partner with engineering teams, analysts, and operational stakeholders. Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience. Nice-to-Have Skills Experience working with manufacturing, MES, quality, or operational data. Familiarity with Fivetran connector management and ingestion architecture. Experience with data contracts and schema governance. Experience building semantic layers or governed analytical datasets. Exposure to modern analytics tools (Hex, Tableau, Power BI, or similar). Experience enabling AI or advanced analytics use cases on top of operational data. Knowledge of streaming or near‑real‑time data pipelines. #J-18808-Ljbffr