Data Analyst

Business Rules & Requirements Definition • Partner with stakeholders to define business rules (e.g., classifications, KPI logic, event definitions) and translate them into clear, testable requirements. • Lead requirements discussions and document definitions, assumptions, edge cases, and acceptance criteria. • Support development by clarifying requirements during implementation and validating outcomes against business intent. Documentation & Knowledge Management • Maintain structured documentation (rule catalogs, metric definitions, mapping specifications, validation checklists) in a format accessible to the broader team. • Document features, modules, requirements, and the risks of each project. Validation & Quality Assurance • Collaborate with data engineers and the testing engineer to validate outputs and support UAT and production readiness. • Identify opportunities to standardize definitions and improve data quality and usability. Collaboration & Stakeholder Engagement • Collaborate with cross-functional stakeholders including ZTD Infrastructure, IT, business, and Information Security teams to evolve technology solutions. • Work closely with business partners to deliver as expected in a timely manner and cost-effective way. • Engage and collaborate with technology partners and industry forums to stay abreast of technology trends, applying them as per business needs. Data Analysis & Insights • Analyze animal health data (dairy preferred) to identify patterns, trends, and anomalies that inform business decisions. • Translate stakeholder needs into clear, testable requirements and communicate effectively with technical teams. • Support converting business needs into technical requirements and scope, design, implement, and review KPIs.

Education: • Bachelor's degree in Computer Science, Computer Engineering, Data Analytics, Business Analytics, or a relevant field. Required Experience: • 3+ years of experience in a Data Analyst, Business Analyst, BI Analyst, or similar role. • Professional experience working with life science domain • Demonstrated experience working in a software/data development lifecycle (e.g., requirements, acceptance criteria, UAT support). • Strong ability to translate stakeholder needs into clear, testable requirements and communicate effectively with technical teams. • Strong SQL skills and experience working with large datasets. • Familiarity with modern data environments and tooling (e.g., Databricks, ETL/ELT concepts, Azure, ADF, Python). • Experience with governed data environments and well-defined metric/rule management practices. Preferred Qualifications: • Experience with Spark/Delta optimization (partitioning, file sizing, performance tuning). • Experience in healthcare/Life Sciences is preferred but not required. • Knowledge/experience in DevOps and Agile methodologies.