Remote Data Engineer
Summary
Remote data engineer (10 years' experience) who must be local to Santa Clara, designing and optimizing analytical datasets and building scalable batch and streaming data pipelines. Core stack is GCP (BigQuery, Cloud Storage, Dataflow/Beam, Pub/Sub) with expert Python, advanced SQL, and Airflow-based orchestration plus CI/CD.
Remote Data Engineer needs 10 years experience
Remote Data Engineer requires:
Must be local top Santa Clara
Cloud Platform Expertise (GCP Focus): Extensive hands-on experience working in dynamic cloud environments, with a strong preference for Google Cloud Platform (GCP) services, specifically:
BigQuery: Expert-level skills in data ingestion, performance optimization, and data modeling within a petabyte-scale environment.
Experience with other relevant GCP services like Cloud Storage, Cloud Dataflow/Beam, or Pub/Sub
Programming & Querying:
Python: Expert-level programming proficiency in Python, including experience with relevant data engineering libraries
SQL: A solid command of advanced SQL for complex querying, data processing, and performance tuning.
Data Pipeline Orchestration: Prior experience using workflow management and orchestration tools (e.g., Apache Airflow, Cloud Composer, Airflow,Dagster, or similar).
DevOps/CI/CD: Experience with version control (Git) and familiarity with CI/CD practices and tools (e.g., GitLab, GitHub Actions) to automate deployment and testing processes.
DevOps/CI/CD, Data Pipeline Orchestration:, SQL, Cloud Platform Expertise (GCP Focus):, Cloud Storage, Cloud Dataflow/Beam, or Pub/Sub
Remote Data Engineer duties:
Design, implement, and optimize clean, well-structured, and performant analytical datasets to support high-volume reporting, business analysis, and data science model development.
Architect, build, and maintain scalable and robust data pipelines for diverse applications, including business intelligence, advanced analytics
Implement and support Big Data solutions for both batch (scheduled) and real-time/streaming analytics.
Work closely with product managers and business teams to understand data requirements and translate them into technical solutions.