Description

What you will be doing:

• Semantic & Reporting Layer Development: Design and maintain a curated semantic layer that standardizes business metrics, definitions, and hierarchies ensuring consistent, governed, and reusable data access across all BI and analytics consumers.
• Data Modeling: Build and optimize robust dimensional and analytical data models (star/snowflake schemas, aggregated layers) that support performant, scalable reporting across diverse use cases.
• Performance Tuning: Identify and resolve query performance bottlenecks through indexing strategies, materialized views, query optimization, caching configurations, and push-down SQL techniques.
• Security Implementation: Implement and enforce row-level security (RLS), role-based access control (RBAC), and data masking policies within the semantic layer and BI platforms to ensure data is accessed only by authorized users.
• Collaboration: Partner with Product, Data Engineering, and Client Success teams to translate business requirements into production-ready data models and analytics deliverables.
• Data Quality & Validation: Perform exploratory data analysis and validation to ensure accuracy, consistency, and trust in all published metrics and insights.
• Documentation: Document semantic layer definitions, data models, security policies, and implementation patterns to support adoption, auditability, and long-term maintainability.
• Dashboard & Report Development: Design and deliver dashboards, KPI scorecards, and embedded analytics using Bold BI, Reveal BI, and other enterprise BI tools, with a strong emphasis on speed to value and stakeholder adoption.
• Document analytics assets and implementation patterns to support adoption and maintainability.
• A well-structured, governed semantic layer serves as the single source of truth for all reporting and analytics consumers. 
• Data models are clean, performant, and extensible — reducing ad hoc rework and enabling faster future delivery. 
• Security policies are consistently enforced at the data layer, ensuring compliance and appropriate data access across user roles. 
• Dashboards and reports built in Bold BI and Reveal BI are scalable, reusable, and trusted by stakeholders. 
• Time-to-delivery decreases through standardization, reusable models, and template-driven builds.

Requirements & Qualifications

• 5+ years of experience in analytics engineering, business intelligence, or data consulting roles.
• Demonstrated experience building semantic or reporting layers (e.g., using dbt, LookML, Power BI datasets, or similar modeling frameworks). 
• Strong SQL skills with deep proficiency in query optimization, transformation logic, and data validation.
• Solid data modeling experience — dimensional modeling, star/snowflake schemas, and aggregation strategies. 
• Experience implementing row-level security, RBAC, and data access governance within BI platforms or data warehouses. 
• Hands-on experience with Bold BI, Reveal BI, or similar modern/embedded BI platforms.
• Familiarity with cloud data platforms (e.g., Redshift, Snowflake) and performance tuning within those environments.
• Experience supporting embedded or multi-tenant analytics use cases is a strong plus. 
• Strong communication skills with the ability to translate complex data structures into accessible business insights. 
• Bachelor's degree in a technical, quantitative, or business discipline (or equivalent experience)

Soft Skills:

• Exceptional Communication: Articulate complex analytical insights and data- driven narratives effectively to both technical and non-technical stakeholders, including the creation of clear Standard Operating Procedures (SOPs).
• Proactive Ownership: Demonstrate initiative by leading the adoption of new processes and independently managing small-scale system enhancement projects from conception to completion.
• Analytical Problem-Solving: Employ a systematic approach to interpret data trends, troubleshoot reporting and visualization issues, and recommend pragmatic, effective process improvements.
• Meticulous Attention to Detail: Uphold the highest standards of data quality and report accuracy through rigorous validation and a detail-oriented approach to all deliverables.
• Stakeholder Engagement: Collaborate effectively with cross-functional teams, including Product and Data Engineering, to understand user pain points and translate business requirements into technical solutions.
• Facilitation and Mentorship: Confidently facilitate virtual training sessions and host technical office hours to support user adoption and enhance data literacy across the organization.

Why you will love Lean Tech:

• Join a powerful tech workforce and help us change the world through technology
• Professional development opportunities with international customers
• Collaborative work environment
• Career path and mentorship programs that will lead to new levels.