Senior Engineer_Data Engineer_7

We are looking for a skilled Data Engineer to join our team and support the build-out of scalable, reliable data infrastructure on the Google Cloud Platform. In this role, you will work on migrating data from Teradata to BigQuery, building and maintaining end-to-end data pipelines, and ensuring data quality and integrity throughout the platform. You will collaborate closely with data analysts, architects, and business stakeholders to translate requirements into robust, production-ready solutions.

Responsibilities

Write efficient, optimized SQL queries to extract, clean, transform, and analyze large and complex datasets from multiple sources; Automate repetitive data workflows and reporting processes to improve efficiency and reduce manual effort; Document methodologies, code, and findings clearly for reproducibility and knowledge sharing; Execute migration tasks under the guidance of senior engineers and architects; Build ingestion scripts, transformation logic, and end-to-end data pipelines; Support migration of data from Teradata to BigQuery; Implement pipeline monitoring, logging, and alerting to ensure reliability; Support testing, validation, and reconciliation of migrated datasets to ensure data integrity; Maintain and update technical documentation and operational runbooks; Collaborate with cross-functional teams including data analysts, architects, and business stakeholders to understand requirements

Requirements

Strong SQL and Python skills; Basic-to-intermediate experience with GCP services, including BigQuery, GCS, Composer, and Cloud Functions; Solid understanding of ETL/ELT data flows and pipeline design; Experience working with APIs, file-based ingestion, and orchestration tools; Ability to test, validate, and debug data pipelines effectively; Hands-on exposure to migration tools such as Storage Transfer Service, gsutil, and bq CLI; Understanding of Teradata-to-GCP mapping concepts (e.g., Teradata → GCS, ADF → Composer); Familiarity with CI/CD concepts and practices; Exposure to version control systems such as Git for code management and collaboration; Understanding of data security, access controls, and governance best practices in cloud environments; Familiarity with data quality frameworks and reconciliation techniques; Good communication and problem-solving skills, with the ability to work independently and in a team setting

Nice to have

Working knowledge of Spark via Dataproc; Prior experience with large-scale data migration projects from on-premise or legacy systems to cloud platforms; Exposure to data cataloging or metadata management tools

Benefits

Health, dental, vision, life insurance, and disability plans; 401(k) Plan; 11 paid holidays; 12 weeks of Parental Leave; Free time PTO policy; Discretionary bonus