Analytics Engineer (Remote)

Job Description
The Analytics Engineer is a crucial role within our company, tasked with the design, development, and maintenance of an enterprise data platform tailored to the needs of a clinical trials business. The role requires an individual who combines the technical ability to execute complex data product development throughout the product lifecycle and the communication and leadership skills to become a trusted partner among the wider business. The Analytics Engineer needs to have the ability to leverage the latest technologies will empower them to deliver on their ambitious goals.
Essential Duties and Responsibilities:
Including, but not limited to the following:
Design and implement robust data pipelines using the best available tooling, meeting all data quality and freshness requirements, provisioning and managing cloud compute resources using infrastructure-as-code, where necessary.
Adopt a DataOps mindset, continuously improving our processes, data platform design and tooling, to ensure that system maintenance and monitoring work is minimized as system complexity increases.
Establish and enforce data governance policies and practices to ensure data integrity, security, and compliance with regulatory standards relevant to patient data.
Collaborate effectively with technical (analytics, data science, IT) and non-technical teams (marketing, clinical) to ensure that their operational and analytical data needs are met from requirements definition, through implementation and delivery of final data products.
Demonstrate technical leadership, researching and integrating the latest data tooling and best practices into development processes. Produce clear and precise documentation, offer mentorship to more junior members and technical guidance across the business to maximize the impact of your expertise.
Data Integration and ELT Processes:
Develop and manage ELT (Extract, Load, Transform) processes that ensure timely and accurate data availability across systems.
System Customization and Integration:
Execute data responsibilities including data preparation, data modeling, and reporting.
Technical Leadership:
Provide technical guidance and leadership in the planning and execution of data projects, ensuring adherence to best practices and quality standards.
Stakeholder Communication:
Communicate effectively with both technical and non-technical stakeholders, translating complex data concepts into understandable terms and actionable insights.
Continuous Learning and Improvement:
Stay updated on emerging data technologies, methodologies, and regulatory requirements, applying this knowledge to drive continuous improvement.