Role and Responsibilities:

Core Analytics Engineering

• Take data compiled by data engineers and clean it in compliance with data hygiene best practices
• Organize and transform data in a meaningful way, providing additional context to make it ready for analysis
• Work with data engineers to streamline upstream processes so that data is cleaner earlier in the pipeline
• Maintain documentation related to datasets and analysis, ensuring consistent language and definitions across the data team
• Build and maintain complex databases in partnership with the technology team
• Create integrated views of data collected from multiple sources
• Develop and use tools, algorithms, and processes for data mining and data visualization to generate decision-ready reports
• Train business analysts and key stakeholders to use various data tools effectively
• Discover opportunities for the organization to improve systems, enterprises, and processes through the use of data analytics

AI-Assisted Development & Automation Tooling

• Use AI-powered tools and automation platforms (e.g., Claude, ChatGPT, GitHub Copilot, or similar) as active parts of the engineering workflow — accelerating data transformation, SQL development, pipeline troubleshooting, and documentation
• Apply AI tooling to automate repetitive tasks such as data profiling, schema documentation, anomaly flagging, and test case generation
• Continuously evaluate and adopt emerging AI tools that improve the speed, quality, and consistency of analytics engineering work
• Share AI productivity practices with teammates to raise the overall capability of the data team

MCP-Enabled BI Integrations

• Configure and maintain MCP (Model Context Protocol) connections between data sources and BI/visualization tools such as Qlik, Tableau, or equivalent platforms
• Ensure MCP-connected data contexts are well-structured, performant, and aligned with organizational data governance standards
• Collaborate with BI developers and data consumers to troubleshoot, optimize, and expand MCP-based integrations as reporting needs evolve
• Document MCP configurations and integration patterns to support team scalability and knowledge transfer

Prompt-Based BI & Report Development

• Use conversational AI tools (e.g., Claude, ChatGPT) to accelerate the development of BI reports, dashboards, and data visualizations through prompt-based workflows
• Translate business requirements into well-structured prompts that produce accurate SQL, data models, chart specifications, and report logic
• Iterate on and refine AI-generated outputs — validating against source data, applying domain knowledge, and ensuring results meet accuracy and compliance standards
• Build and maintain a library of reusable prompts for recurring reporting needs (e.g., adherence reporting, patient risk summaries, formulary analysis) to promote consistency and efficiency
• Document prompt-to-report workflows so that patterns can be shared, reviewed, and reused across the data team

Qualifications and Requirements:

• Positive and solution-oriented mindset
• Comfort working in a highly agile, intensely iterative environment
• Self-motivated and self-managing, with strong task and project organizational skills
• Great communication: regularly achieve consensus among technical and business teams
• Demonstrated capacity to communicate complex technical requirements and recommendations clearly and concisely
• Extensive experience in the healthcare and pharmaceutical industry
• Demonstrated experience in one or more business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people operations
• 6+ years in the data space as an analyst, engineer, scientist, or equivalent
• 4+ years designing, implementing, operating, and extending commercial Kimball enterprise dimensional models
• 4+ years working with a large-scale Data Warehouse in a cloud environment
• 2+ years building reports and dashboards in a data visualization tool
• 1+ years actively using AI tools (LLMs, code assistants, or AI-powered automation) as part of a professional data or analytics workflow
• 1+ years working with MCP-based or equivalent connector/integration configurations within BI platforms
• 1+ years using prompt-based development techniques to generate or accelerate production-quality SQL, data models, or reports
• 1+ years creating project plans to identify tasks, milestones, and deliverables
• Demonstrated experience leading 4+ analytics projects from inception to operationalization
• Demonstrated experience designing and socializing Entity Relationship Diagrams and reference SQL scripts to scale data acumen and adoption
• Experience working with multiple cloud data warehouses, ETL tools, and data visualization technologies
• Bilingual in Spanish and English

Preferred Experience:

• Experience with AWS, Snowflake, Talend, Tableau, or Qlik
• Hands-on experience using Claude, ChatGPT, GitHub Copilot, or similar AI assistants in a data engineering or analytics context
• Familiarity with MCP server/client configurations within Qlik or comparable BI tools
• Background in healthcare data standards (HL7, FHIR, NCPDP) and data privacy requirements in regulated environments
• Prior experience documenting and socializing AI-assisted development workflows with a broader team

Originally posted on Himalayas