Senior Data Engineer 3468

Ready; United States; Remote; USD 130,000 - 170,000; Full time

Job summary

Ready is seeking a Senior Data Engineer to design, implement, and maintain high-impact data pipelines on Google Cloud Platform. You will work with BigQuery, Dataform, and Python to deliver scalable data products and analytics-ready datasets.

Join a team that values architectural judgment, autonomy in remote environments, and close collaboration with business and engineering teams to translate requirements into robust solutions.

Qualifications

• 5+ years of experience in data engineering with pipelines and data architectures.
• Advanced mastery of BigQuery and Dataform for building data models and transformations at scale.
• Solid experience with Google Cloud Platform services including Pub/Sub and Cloud Storage.

Responsibilities

• Design scalable and efficient data pipelines on Google Cloud Platform, ensuring quality, traceability, and performance at every stage of the workflow.
• Implement end-to-end data pipelines on Google Cloud Platform, from ingestion through data availability for analytical consumption.
• Maintain, monitor, and optimize existing data pipelines and products on Google Cloud Platform, identifying opportunities for continuous improvement.
• Develop data transformations and models with primary focus on BigQuery and Dataform, ensuring consistency, efficiency, and maintainability of SQL and Python code.
• Integrate and consume external and internal APIs for data ingestion and enrichment within processing workflows.
• Actively collaborate with business and software engineering teams to translate functional requirements into robust and well-documented technical solutions.
• Define and apply data engineering best practices: versioning, testing, documentation, and dependency management in production pipelines.

Skills

Autonomy

APIs integration

Python

Tools

BigQuery

Dataform

Google Cloud Platform

Pub/Sub

Cloud Storage

REST APIs

Job description

We are looking for a Senior Data Engineer with solid experience in Google Cloud Platform to design, implement, and maintain high-impact data pipelines and products. The role demands technical autonomy, architectural judgment, and the ability to work closely with business and engineering teams. If you master BigQuery, Dataform, and Python, and enjoy solving complex data challenges in cloud environments, this position is for you.

• Design scalable and efficient data pipelines on Google Cloud Platform, ensuring quality, traceability, and performance at every stage of the workflow.

• Implement end-to-end data pipelines on Google Cloud Platform, from ingestion through to data availability for analytical consumption.

• Maintain, monitor, and optimize existing data pipelines and products on Google Cloud Platform, identifying opportunities for continuous improvement.

• Develop data transformations and models with primary focus on BigQuery and Dataform, ensuring consistency, efficiency, and maintainability of SQL and Python code.

• Integrate and consume external and internal APIs for data ingestion and enrichment within processing workflows.

• Actively collaborate with business and software engineering teams to translate functional requirements into robust and well-documented technical solutions.

• Define and apply data engineering best practices: versioning, testing, documentation, and dependency management in production pipelines.

Requirements

• 5 or more years of experience in data engineering, with proven participation in production projects involving pipelines and data architectures.

• Advanced mastery of BigQuery and Dataform for building and orchestrating data models and transformations at scale.

• Solid experience with Google Cloud Platform services, including Pub/Sub and Cloud Storage, in contexts of data ingestion, processing, and storage.

• Advanced handling of Python for automation, data processing, and pipeline development, along with advanced SQL oriented toward analytics and complex transformations.

• Experience in consuming and integrating REST APIs for data ingestion and enrichment workflows.

• Ability to work autonomously in remote environments, managing priorities and deliverables with independent judgment and without constant supervision.