Sr. Analytics Engineer
Nature Sunshine
- Lehi, UT
- Permanent
- Full-time
- Architect and Build: Navigate a complex landscape of internal processes, data sources, and business models to establish a robust data warehouse for NSP's financial data
- Collaborate with Stakeholders: Partner with analysts and business stakeholders to translate their data needs into technical requirements and effective data models
- Implement ETL/ELT Processes: Collaborate with data engineers to design and execute ETL/ELT processes to feed the data lake and produce structured datasets that facilitate high-quality analysis
- Optimize Data Models: Design, maintain, and optimize data models in SQL, Power BI, and other tools, to drive impactful reporting and analysis
- Manage Quality: Create and manage data transformation workflows, including cleaning, integration, and validation processes, ensuring high data accuracy and usability
- Create Dashboards: Develop advanced, interactive dashboards and reports in Power BI that provide valuable insights for decision-making
- Maintain Documentation: Produce comprehensive documentation for data structures, transformation logic, and data lineage to enhance transparency and data literacy across the organization
- Enhance Data Integration: Lead the development and maintenance of master data management (MDM) practices to optimize data integration and analytical value
- Project Management: Develop and manage project plans, milestones, and deliverables for data and analytics initiatives, ensuring alignment with business objectives and timelines
- Advocate for Best Practices: Contribute to a culture of high-quality data management by advocating for best practices in data quality, governance, and security
- Bachelor's degree in computer science, data science, engineering, or a related field
- 3+ years of experience in analytics engineering, business intelligence, or data engineering
- Proficiency in designing and managing data warehouses or data lakes
- Strong experience in data modeling (e.g., star schema, snowflake schema), with an understanding of dimensional and relational modeling best practices.
- Familiarity with version control systems (e.g., Git) and collaborative workflow tools.
- Solid SQL expertise
- Proficiency in at least one programming language commonly used in data engineering, such as Python or Scala
- Familiarity with BI tools such as Power BI and the ability to develop and optimize dashboards
- Knowledge of best practices in data management, including data governance, quality, and security
- Familiarity with Azure DevOps and experience working in Agile methodologies is advantageous
- Strong analytical rigor to navigate a complex environment of internal processes, information systems, and business models
- Proactive and highly organized approach to troubleshoot data quality issues, optimize data processes, and ensure accuracy and reliability
- Excellent communication and interpersonal skills, with the ability to work effectively with both technical and non-technical stakeholders
- Experience working in cross-functional teams, collaborating effectively with analysts, engineers, and stakeholders to ensure alignment on objectives
- Ability to prioritize tasks, manage timelines, and handle multiple projects, ensuring timely and organized completion of initiatives