Sr. Analytics Engineer

- Senior

Lehi, UT

Chemical Manufacturing

About the position

We are seeking a senior, experienced analytics engineer to join our team and take charge of designing, building, and optimizing a data warehouse as the single source of truth for all financial data at Nature's Sunshine. This role requires strong expertise in data architecture, ETL/ELT processes, and data modeling, along with proficiency in SQL, Python, and modern analytics tools. You'll collaborate closely with data architects, the financial planning and analysis team, and business process owners, to create robust data pipelines and maintain a reliable analytics infrastructure. Success in this role requires an innovative, problem-solving mindset and the ability to transform complex information into high-quality data models for strategic decision-making.

Responsibilities

• 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

Requirements

• 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

Nice-to-haves

• Familiarity with Azure DevOps and experience working in Agile methodologies is advantageous