Senior Data Engineer

ryancompanies; Minneapolis (MN); Hybrid; USD 115,000 - 144,000; Full time

Job summary

Ryan Companies is seeking a Senior Data Engineer for the Minneapolis headquarters with a 4-days-per-week in-office schedule and one remote day. You will build and maintain data pipelines on GCP, design data models, and support analytics, ML, and decision intelligence across the organization.

You will collaborate with data architects, data scientists, and analysts to deliver scalable data solutions, governance, and CI/CD automation.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
• 5+ years of professional experience in data engineering or a similar role.
• Strong programming skills in Python and SQL, with experience using Cloud Composer.
• Experience designing and maintaining data pipelines on cloud platforms (GCP, AWS, Azure).

Responsibilities

• Architect, build, and maintain scalable data pipelines on Google Cloud Platform (GCP) using BigQuery, Dataflow, and Cloud Storage.
• Design and implement data models, including star schemas and dimensional modeling.
• Develop and manage data warehousing solutions for efficient storage and access.
• Contribute to metadata management, data cataloging, and lineage tracking.
• Design and orchestrate ETL/ELT processes using Cloud Composer or Apache Airflow.
• Write clean Python and SQL code, monitor and optimize pipeline performance.
• Collaborate with data architects, AI/ML engineers, data scientists, analysts.

Skills

Python

SQL

Data pipelines

GCP

Airflow / Cloud Composer

BigQuery

CI/CD

Data Modeling

Education

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems

Tools

Cloud Composer

Apache Airflow

BigQuery

Dataflow

Cloud Storage

GCP

AWS/Azure

Job description

Ryan Companies has an immediate need for a Senior Data Engineer. This is a 4-days-per-week IN-OFFICE opportunity for our Minneapolis headquarters, providing 1 day work-from-home each week.

The Senior Data Engineer will play a foundational role in building and maintaining the data infrastructure that enables advanced analytics, machine learning, and decision intelligence across Ryan Companies. This role will focus on developing scalable, reliable data pipelines that ensure the quality, accessibility, and performance of data used across all of Ryan Companies.

The successful candidate will work cross-functionally with data architects, AI/ML engineers, data scientists, analysts, and domain experts to design and implement modern data engineering solutions.

With more than 88 years in business and 16 offices (and growing!), Ryan offers comprehensive commercial real estate solutions to customers across the US. We bring a collaborative, relationship-driven approach to delivering spaces where people thrive and businesses succeed. Join a company with an outstanding culture and competitive benefits. At Ryan, we don't just build buildings - we build stories.

Some things you can expect to do:

Data Architecture and Modeling

• Architect, build, and maintain scalable data pipelines on Google Cloud Platform (GCP), utilizing services like BigQuery, Dataflow, and Cloud Storage to handle diverse data sources (e.g., project systems, safety logs, IoT/sensor data).
• Design and implement effective data models, including star schemas and dimensional modeling, to support business intelligence and analytics.
• Develop and manage data warehousing solutions to ensure efficient data storage, retrieval, and cost-effectiveness.
• Contribute to metadata management, data cataloging, and lineage tracking to enhance the discovery and transparency of enterprise data assets.

Data Pipeline Development and Management

• Design and orchestrate robust ETL/ELT processes and data integration workflows using tools like Cloud Composer or Apache Airflow.
• Implement and manage both batch and real-time data streaming pipelines to ensure timely and accurate data availability for downstream applications.
• Write clean, efficient, and well-documented Python and SQL code to process and transform large, complex datasets.
• Monitor, troubleshoot, and optimize data pipeline performance, identifying and resolving bottlenecks to improve efficiency and scalability.

Data Quality and Governance

• Implement and maintain data quality frameworks to ensure the accuracy, consistency, and reliability of data across all systems.
• Develop and implement data validation and testing procedures to maintain the highest standards of data integrity.
• Establish and enforce data governance policies and best practices, ensuring all data handling is secure, private, and compliant with regulations.

Platform Engineering and Automation

• Build and maintain CI/CD pipelines for the automated testing and deployment of data engineering workflows.
• Support the deployment and monitoring of machine learning models by implementing reproducible and traceable data environments.
• Partner with DevOps and Technology teams to automate infrastructure provisioning, CI/CD processes, and data quality monitoring.

Collaboration and Leadership

• Partner with Enterprise Architects, Solution Architects, data scientists, and analysts to understand data needs, design technical solutions, and translate business requirements into architectural designs.
• Lead the implementation of data solutions, from discovery and design through to deployment.
• Provide mentorship and guidance to other data engineers, fostering a culture of knowledge sharing and continuous improvement.
• Create and maintain clear documentation for architecture, schemas, and pipeline workflows to support team knowledge and onboarding.

Some things we expect you to have:

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 5+ years of professional experience in data engineering or a similar role.
• Strong programming skills in Python, SQL, with experience using tools such as Cloud Composer.
• Proven experience designing and maintaining data pipelines using platforms such as GCP, AWS, Azure or similar.

You will set yourself apart if you have:

• Experience building data infrastructure and services in cloud-native environments (GCP preferred, with exposure to AWS).
• Familiarity with MLOps or experience supporting machine learning pipelines in production environments.
• Exposure to domain-driven architecture.
• Strong collaboration and communication skills with a track record of partnering across functions to deliver high-impact solutions.

Compensation:

The base pay range is $115,00 - $144,000/Annually. The salary may vary within the anticipated range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may