Data Engineer

Who are we looking for?

A hands-on Data Engineer who builds scalable ELT/ETL pipelines with strong SQL, Python, and Databricks skills. You're collaborative, organized in Agile environments, and passionate about clean data and engineering excellence.

Why Daniels Health?

Daniels Health is a mission-driven global innovator in healthcare waste management, operating across the U.S., Australia, Canada, Europe, and South Africa. We're experiencing significant global growth—expanding our U.S. footprint through key facility acquisitions, strengthening our presence in Europe, and growing operations in Australia, Canada, and South Africa. As a consistently recognized industry leader, we're scaling our data and AI capabilities to power smarter decision-making, seamless integrations, and sustainable innovation across our rapidly expanding global operations.

• Architect and build ELT/ETL pipelines ingesting data from APIs, applications, databases, and SaaS platforms into Databricks


• Own bronze and silver layers using PySpark, SQL, and medallion architecture best practices


• Implement automated testing, monitoring, alerting, and data quality frameworks to ensure pipeline reliability


• Develop reverse ETL pipelines to move curated data back into operational systems


• Partner with Analytics Engineers, BI teams, and stakeholders to define data contracts and integrate new sources


• Champion data governance, security standards, and engineering best practices across the organization

• Success in this role means delivering reliable, well-tested Databricks pipelines for priority data sources, establishing monitoring/alerting and data quality checks, and documenting data contracts so Analytics, BI, and operational teams can confidently use curated datasets (including reverse ETL) to support decision-making and scalable global integrations

• 3+ years of data engineering or software engineering experience


• Advanced SQL and Python expertise with proven ability to write efficient, scalable code


• Hands-on Databricks experience and strong understanding of medallion architecture


• Familiarity with GitHub, version control workflows, and automated testing practices


• Understanding of data quality frameworks and experience working in Agile/Scrum environments


• Special Requirements


• Occasional travel necessary to accommodate for the global and regional meetings / workshops


• Ability to occasionally join calls before / after traditional office hours

Be Part of Daniels Health's Global Growth Story

If you want to build high‑quality data products that drive meaningful outcomes—and you're energized by the idea of supporting a company scaling worldwide—we'd love to meet you.

Apply now and help shape the future of analytics at Daniels Health.

Candidates must currently reside in the United States and be authorized to work without sponsorship.

Daniels Health & Sharpsmart is an equal opportunity employer. In accordance with anti-discrimination law, it is the purpose of this policy to effectuate these principles and mandates. Daniels Health & Sharpsmart prohibit discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, age, national origin, disability status, protected veteran status, or any other characteristic protected by law. Daniels Health & Sharpsmart conforms to the spirit as well as to the letter of all applicable laws and regulations.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.