Data Engineer II

Role Objectives:Data Engineer II is responsible for owning a defined data domain within a business stream, including its data pipelines, models, quality checks, documentation, & production operations. The role works across the Company's BigQuery and Trino + Apache Iceberg lakehouse environments, solving data engineering challenges related to incremental model design, data layout, SQL dialect differences, reliability, and cost optimization.The role operates with a high degree of independence, translating business and analytical requirements into well-scoped technical solutions, defining appropriate acceptance criteria, and owning outcomes through productionRoles & Responsibilities:Own the design, development, and operation of ingestion and transformation pipelines for a defined data domain, including dependencies, sequencing, backfills, and production support.Design reliable and scalable pipelines using appropriate architectural patterns, including idempotency, error handling, retries, recovery, and handling of late or out-of-order data.Design and maintain data models for the assigned domain, applying appropriate modeling patterns, automated tests, and documentation to ensure data quality and usability.Maintain data quality and pipeline reliability through automated testing, monitoring, gap detection, and recovery mechanisms, and resolve issues through root-cause analysis.Partner directly with analysts and business stakeholders to translate requirements into well-scoped technical solutions, define acceptance criteria, and communicate data limitations and dependencies.Partner with Product and Engineering teams to ensure new features and changes generate complete and reliable data for downstream analytics and data products.Diagnose and optimize pipeline and query performance, assessing correctness, scalability, and cost before and after changes.Maintain monitoring, alerting, and runbooks for owned data pipelines, and drive improvements that reduce recurring operational issues and manual effort.Review teammates’ data engineering solutions and code, providing constructive technical feedback and promoting maintainable engineering practices.Collaborate with Data Platform Engineering and other engineering teams on dependencies and infrastructure requirements affecting the owned domain.Required Education, Knowledge, And Skills:2-4 years in data engineering or an adjacent production engineering role.Strong SQL, including performance. You can read a query plan, spot a bad join, and reason about partitioning and data layout.Production Python. Modules, tests, error handling and dependency management, not just scripts.Data modelling for a real domain. Dimensional or equivalent models you designed, with tests and documentation that others relied on.dbt, or an equivalent transformation framework, in production.A workflow orchestrator in production, such as Dagster or Airflow.Git and code review as routine practice.Docker. Building, running and debugging containerised jobs.