BI Analytics Engineer

This is a fully remote position, open to applicants in New York, +1 more state.

📋 Description

• Create, develop, and sustain semantic data models, encompassing facts, dimensions, hierarchies, relationships, and business metrics.

• Establish core architecture, standards, and patterns for scalable enterprise reporting and analytics.

• Collaborate with BI developers, analysts, and stakeholders to convert analytical requirements into reusable data frameworks.

• Define and execute dimensional modeling, manage slowly changing dimensions, historical data, and conformed-dimension standards.

• Build and uphold user-friendly semantic layers for intricate healthcare and product datasets.

• Work together with software engineering, data platform, data engineering, and business teams to ensure model and architecture alignment.

• Implement approved metric definitions and business rules within semantic models.

• Assess and enhance model performance, scalability, and usability for dashboards and self-service analysis.

• Engage in data architecture discussions and offer advice on reporting, analytics, and data consumption strategies.

• Verify data quality and model integrity through testing and monitoring.

• Maintain governance standards for data definitions, metric calculations, documentation, and semantic-layer usage.

• Provide guidance on analytics initiatives focused on long-term scalability and maintainability.

• Expand analytical data models and curated datasets for self-service analytics, AI-assisted data exploration, and emerging data consumption trends.

⛳️ Requirements

• A Bachelor's Degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent experience.

• Over 5 years of experience in analytics engineering, business intelligence engineering, data modeling, data architecture, or a related discipline.

• Extensive experience in designing and implementing dimensional data models, fact and dimension tables, star schemas, and semantic layers.

• Knowledge of data warehouse principles, slowly changing dimensions, historical tracking, surrogate keys, and data lineage.

• Experience in developing and optimizing models for business intelligence and self-service analytics.

• Proficiency in SQL and familiarity with large, complex datasets.

• Experience with modern cloud data platforms like Snowflake, BigQuery, Redshift, Synapse, or Databricks.

• Capability to optimize analytical data structures for performance, scalability, and self-service usage.

• Ability to translate analytical requirements into scalable technical solutions in partnership with business stakeholders.

• Strong understanding of data governance, metric standardization, and analytical best practices.

• Experience working collaboratively with software engineering, data engineering, and analytics teams.

• Ability to balance technical design with business usability and accessibility needs.

• Excellent written and verbal communication skills suitable for both technical and non-technical audiences.

• Prior experience with healthcare data, product data, or other complex domain-specific datasets is preferred.

• Familiarity with supporting Power BI or Tableau semantic models, tabular models, or equivalent BI technologies is preferred.

🏝️ Benefits

• Health and welfare benefits.

• Incentive plans, bonuses, and/or other forms of compensation may be offered.