[Hiring] Analytics Engineer @Hyland

Role Description

The Analytics Engineer provides clean data sets and models data in a way that enables analysis to drive key business insights. In this role, you'll partner with business users to answer critical questions through data-driven analysis, while leveraging a solid understanding of data infrastructure and tooling to monitor and maintain data pipelines and develop reliable data transformations.

• Collaborate with team members to collect business requirements, define successful analytics outcomes, and design data models while considering performance, cost, and security constraints.
• Model, design, develop, test, and implement backend and front-end structures needed to meet business visualization and reporting requirements.
• Configure SaaS tools — including ELT providers, integration platforms, and orchestration tools — to build a modern cloud data warehouse that is accurate, reliable, high-performing, and accessible across business departments.
• Provide day-to-day support of the data warehouse and associated data marts, including establishing trusted data sets with clear, supporting documentation.
• Coordinate with platform data engineering, data analyst, data governance, and IT teams to align with change management processes and ensure optimal performance and access for global reporting solutions.
• Improve data flow and quality processes to enhance data accuracy, viability, and value — including testing data transformations to ensure correspondence to defined tasks.

Qualifications

• Bachelor's degree or equivalent experience.
• Extensive experience working as part of a data team, preferably as a data engineer or data analyst.
• Strong SQL skills and hands-on data transformation expertise.
• Proven experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and cloud platforms (AWS, Azure, GCP).
• Hands-on experience with modern BI tools such as Looker, Mode, Tableau, or Power BI.

Requirements

• Experience with data modeling tools such as Dataform or dbt for data transformation workflows.
• Demonstrated proficiency in data system design including databases, schemas, marts, aggregates, and views.
• Experience in one or more major data subject areas (Product, Marketing, Sales, Finance, People, etc.).
• Strong project management and organizational skills with the ability to drive initiatives to completion with minimal oversight.
• Ability to apply original thinking to translate business goals into innovative, scalable data solutions.

Technology Tools

• Cloud Platforms: AWS, Azure, GCP
• Cloud Data Warehouses: Snowflake, BigQuery, Redshift
• BI Tools: Looker, Mode, Tableau, Power BI
• Data Modeling Tools: Dataform, dbt
• Other: SQL, Microsoft Excel, Microsoft Office