Senior Data Engineer
mattel
Job Description
- Lead the development of scalable, secure, and high-performing data integration pipelines for structured and semi-structured data using Google BigQuery.
- Design and develop scalable data integration pipelines to ingest structured and semi-structured data from enterprise systems (e.g., ERP, CRM, E-commerce, Order Management) into a centralized cloud data warehouse using Google BigQuery.
- Build analytics-ready pipelines that transform raw data into trusted, curated datasets for reporting, dashboards, and advanced analytics.
- Implement transformation logic using DBT to create modular, maintainable, and reusable data models that evolve with business needs.
- Apply BigQuery best practices—including partitioning, clustering, and query optimization—to ensure high performance and scalability.
- Automate and monitor complex data workflows using Airflow/Cloud Composer, ensuring dependable pipeline orchestration and job execution.
- Develop efficient, reusable Python and SQL code for data ingestion, transformation, validation, and performance tuning across the pipeline lifecycle.
- Establish robust data quality checks and testing strategies to validate both technical accuracy and alignment with business logic.
- Partner with architects and Technical leads to establish best practices, scalable frameworks, and reference implementations across projects.
- Collaborate with cross-functional teams—including data analysts, BI developers, and product owners—to understand integration needs and deliver impactful, business-aligned data solutions.
- Leverage modern ETL platforms such as Ascend.io, Databricks, Dataflow, or Fivetran to accelerate development and improve observability and orchestration.
- Contribute to technical documentation, CI/CD workflows, and monitoring processes to drive transparency, reliability, and continuous improvement across the data engineering ecosystem.
- Mentor junior engineers, conduct peer code reviews, and lead technical discussions.