Job Description
5–9 years of overall experience in data engineering / analytics engineering 3+ years of hands-on experience with GCP BigQuery Strong proficiency in SQL (BigQuery dialect preferred) Experience with Google Cloud Platform (GCP) services, such as: BigQuery Cloud Storage Dataflow / Dataproc (good to have) Solid understanding of data warehousing and analytics concepts Experience with batch and near real-time data processing Familiarity with data modeling techniques and large-scale datasets Experience with Python or Shell scripting (preferred) Knowledge of Git and CI/CD practices Strong analytical, debugging, and communication skills
Design, develop, and optimize data models and datasets in Google BigQuery Write and optimize complex SQL queries, views, and stored procedures in BigQuery Build and maintain ETL/ELT pipelines using GCP services Ingest and process large-scale structured and semi-structured data Implement data transformations using BigQuery SQL and cloud-based data processing tools Optimize query performance and cost using partitioning, clustering, and query optimization techniques Integrate data from various sources including cloud storage, databases, APIs, and streaming sources Work with Cloud Storage, Dataflow, Dataproc, or similar services Ensure data quality, consistency, and reliability Collaborate with BI, analytics, and business teams to meet data requirements Support CI/CD, deployment, and monitoring of data pipelines
GCP certifications (Professional Data Engineer / Associate Data Engineer) Experience with Looker, Data Studio, or other BI tools Agile/Scrum working experience
