Job description

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 $115,000 - $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 be eligible for additional compensation that may include commission and/or an incentive program. Eligibility: Position requires verification of employment to work in the U.S. Benefits: Competitive Salary Medical, Dental and Vision Benefits Retirement and Savings Benefits Flexible Spending and Health Savings Accounts Life Insurance Short-Term and Long-Term Disability Educational Assistance Paid Time Off (PTO) Employee Assistance and Wellness Programs Parenting Benefits Employee Discount Programs Pet insurance Ryan Foundation – charitable matching funds Paid Time for Volunteer Events Disclaimer: Eligibility may vary based on factors such as role, hours worked, employment status, length of service, location, and other considerations. Detailed information will be shared with eligible candidates during the hiring process, and the official terms and conditions will be outlined in each individual offer document. Ryan Companies is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Notice to Candidates: Please be advised that initial outreach regarding employment at Ryan Companies will only occur via email from the domain ryancompanies.com email address. If you recieve communication from someone you believe is impersonating Ryan Companies, please report it to us at humanresources ryancompanies.com Non-Solicitation Notice to Recruitment Agencies: Ryan Companies kindly requests that recruitment agencies and third-party recruiters do not submit unsolicited resumes or candidate information to any Ryan Companies employee or office. Ryan Companies will not be responsible for any fees or expenses associated with unsolicited submissions. If recruitment services are required, we will reach out directly to agencies on our approved vendor list. We appreciate your understanding and cooperation.

Requirements

Must-haves

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 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.
Data Architecture and Modeling
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.

Nice-to-haves

Experience building data infrastructure and services in cloud-native environments (GCP preferred, with exposure to AWS).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaccessibilityaimlgcppythonsqlci/cdawsazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Wellness