Data Engineer with BigQuery, Real Time Warehouse Platform

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Project overview

We are building a modern data warehousing platform that supports both real time and batch analytical workflows. The project focuses on designing scalable data pipelines, implementing a medallion architecture, and enabling seamless collaboration across data engineering, analytics, and data science teams.

Team

You will collaborate with a cross functional team of data engineers, data scientists, and analysts. The team follows an open communication style, uses Agile practices, and works closely to define data requirements and deliver scalable solutions.

Position overview

We are looking for a Data Engineer who will design, develop, and optimize data pipelines and warehouse layers on Google BigQuery. You will work with real time streaming, batch processing, and MLflow based workflows while ensuring data quality, reliability, and performance across all components of the platform.

Technology stack

Google BigQuery, Google Cloud Pub/Sub, Apache Beam, Dataflow, Cloud Composer, Apache Airflow, Python, SQL, MLflow, Terraform, Great Expectations, dbt tests

Responsibilities

Plan, develop, and maintain ETL and ELT pipelines across Bronze, Silver, and Gold layers
Implement the medallion architecture with a focus on data lineage and quality
Build and optimize real time data streaming pipelines using Pub/Sub and Apache Beam on Dataflow
Create and orchestrate batch workflows using Cloud Composer and Apache Airflow
Write performant and cost efficient BigQuery SQL using partitioning, clustering, and query optimization
Collaborate with analysts and data scientists to understand data needs and deliver reliable solutions
Prepare and maintain technical documentation, data dictionaries, and monitoring dashboards

Requirements

4 years of Data Engineering experience
3 or more years of experience designing and building cloud based ETL and ELT pipelines
Hands on experience with data modeling including dimensional modeling and schema design
Experience working with real time streaming architectures and event driven data processing
Proficiency in SQL and at least one programming language such as Python, Java, or Scala
Experience with Google Cloud Pub/Sub for message driven ingestion
Practical experience building Apache Beam pipelines on Google Cloud Dataflow
Experience with workflow orchestration in Cloud Composer or Apache Airflow
Hands on experience with optimizing BigQuery SQL, partitioning, clustering, resource usage, and cost management

Nice to have

Experience using BigQuery ML for model creation and deployment
Foundational understanding of machine learning workflows and feature engineering
Experience with Terraform for infrastructure provisioning
Familiarity with data quality frameworks such as Great Expectations or dbt tests
Google Cloud Professional Data Engineer certification

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