POSITION SUMMARY:

As a Senior Analytics Engineer, you will play a critical role in designing and developing scalable data models and pipelines that empower our business with actionable insights. Embedded within the Analytics and Data Services organization, you will collaborate with cross-functional teams and stakeholders across the organization—to solve complex data challenges and drive innovation in our data platform.
You will act as a bridge between technical and non-technical teams, ensuring that data models are robust, data quality is high, and insights are accessible. This role is integral to fostering a culture of data-driven decision-making across the organization.

QUALIFICATIONS AND EDUCATION REQUIREMENTS:

• Education: Bachelor’s degree in a related field (e.g., Statistics, Computer Science, Mathematics) or equivalent industry experience. Advanced degrees are preferred but not required. Advanced certifications in data analysis or data governance (e.g., CDMP, CBIP) are a plus.
• Experience: 5-9+ years of experience in data engineering, analytics engineering, or BI engineering, with proven experience in building and optimizing data models and pipelines. Strong understanding of data governance, data quality, and analytics best practices. Experience with modern BI tools like Sigma, Power BI, or Tableau. Expertise in predictive modeling, statistical analysis, and developing business-aligned metrics.
• Technical Skills: Expertise in SQL, Python, and Spark for ETL/ELT processes. Proven experience in designing and deploying complex data architectures in cloud environments (AWS, GCP, or Azure), modern data architectures (data lakes, warehouses, mesh), and tools such as dbt, Airflow, and Databricks. Experience with large-scale data warehouses (e.g., Snowflake, Redshift, BigQuery) and streaming data systems.
  All new hires are required to attend New Collaborator Orientation (NCO) in Salt Lake City, Utah. The College will pay for travel and lodging accommodations.
  Nightingale’s commitment to diversity and inclusion is reflected both in our learners and collaborators because we believe the best outcomes for learners from underserved and diverse populations are achieved through collaborators with similar backgrounds and cultures. Nightingale College is an equal opportunity employer.
  Our Mission (not just words on the wall, we live it, love it, and daily contribute to it): With the primary focus on higher learning in healthcare professions, Nightingale College contributes to elevating education, health, and employment systems through facilitation of academic achievement, personal growth, and professional development of its learners, alumni, and collaborators, while serving diverse communities.
  At Nightingale College, our Innovative Education model helps transform rural health landscapes through our blended-distance learning platform. Every person involved with Nightingale College helps to change the lives of our learners, our communities, and ultimately the world by adding to the quality of healthcare. We are proud to have graduated over 3,400 nurses serving communities in need. We are serious about our outcomes and have a little bit of fun getting there.
  The professional and personal development of our learners and our collaborators is our company’s foundation. Not only do we develop strategies that promote a positive work-life integration, but we also create an environment that invites you to become an expert in your field, be it through higher education or professional development. Put simply, we elevate employment, elevate health, and elevate education. We’re so happy that you’ve found us

• Data Modeling & Pipelines: Architect and develop data models and curated datasets that form the foundation of analytics and reporting. Partner with Data Engineers to build efficient, scalable, and cost-effective data pipelines.
• Collaboration & Partnership: Work closely with business analysts, data scientists, and cross-functional teams to understand data requirements and ensure data models and pipelines meet the business’s evolving needs.
• Analytics Enablement: Educate and empower stakeholders to utilize data assets and BI tools effectively (e.g., Sigma, Tableau, Power BI). Support self-service analytics and create data products that meet business objectives.
• Data Governance & Quality: Implement and enforce data integrity standards and best practices to ensure data is consistent, accurate, and reliable. Develop observability automation to monitor the quality of both batch and real-time data streams.
• End-to-End Solution Design: Lead the design and execution of scalable solutions that transform raw data into actionable insights, focusing on performance, cost-effectiveness, and adaptability.
• Innovation & Automation: Utilize advanced technologies (e.g., dbt, Airflow, Airbyte, Fivetran) to optimize ETL/ELT pipelines. Collaborate with platform engineering teams to co-design new workflows and capabilities.
• Predictive & Advanced Analytics: Leverage statistical methods, machine learning models, and advanced analytics to build predictive features and metrics that align with business goals.