BigQuery Data Engineer

As a Data Engineer at DataNimbus, you will play a crucial role in shaping a sustainable, AI-driven future by working with cutting-edge technologies and revolutionizing workflows in Data+AI solutions. Your contributions will be trusted by global businesses for their scalability, security, and efficiency, allowing you to grow personally and professionally in a culture that values curiosity and continuous learning. **Key Responsibilities:** - Design, develop, and maintain a highly scalable data warehouse solution in BigQuery. - Architect data models, schemas, and partitioning strategies for efficient query performance. - Build and maintain ETL/ELT pipelines using tools such as Dataflow, Dataproc, Cloud Composer (Airflow), or dbt. - Optimize query performance and manage cost-efficient BigQuery usage. - Implement data governance, security, and compliance best practices (IAM, data masking, audit logging). - Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable, high-quality datasets. - Ensure data quality and consistency through monitoring, validation, and testing. - Mentor junior engineers and contribute to best practices, coding standards, and documentation. **Qualifications:** - 6+ years of experience in Data Engineering, with at least 3+ years working on BigQuery in a production environment. - Strong SQL expertise, including query optimization and advanced SQL features. - Proficiency in at least one programming language (Python, Java, or Scala). - Experience with cloud data ecosystem (Google Cloud Platform preferred). - Strong understanding of data modeling, star/snowflake schemas, and OLAP concepts. - Hands-on experience with ETL/ELT frameworks and workflow orchestration tools (Airflow, Cloud Composer, dbt). - Knowledge of data governance, lineage, and security practices. - Familiarity with streaming/batch data ingestion (Pub/Sub, Kafka, or equivalent). - Exposure to machine learning workflows in BigQuery ML. - Experience with BI/visualization tools such as Looker, Tableau, or Power BI.,