Senior Staff Engineer – Data Analytics

This is a fully remote position, open to applicants in Florida.

📋 Description

• Create, develop, test, and sustain production-level analytical data models utilizing dbt and Databricks.

• Construct scalable Gold-layer models that convert operational data into analytical datasets ready for business use.

• Design dimensional, domain-focused, and reusable data models for reporting, analytics, and downstream data products.

• Ensure a clear distinction between raw/curated data, Gold analytical models, and the enterprise semantic layer.

• Execute testing, documentation, lineage, version control, and deployment practices for analytical data assets.

• Create and refine semantic models to ensure consistent business metrics, dimensions, and KPIs.

• Establish analytical foundations that are optimized for Tableau and other BI or self-service tools.

• Centralize reusable definitions while minimizing duplicated business logic across dashboards, reports, and analyst workflows.

• Collaborate with analysts and business teams to convert business concepts into governed analytical models.

• Treat analytical datasets, semantic models, and reusable metrics as managed data products.

• Develop reusable data products for various downstream consumers.

• Work alongside product, analytics, engineering, and business teams to identify and prioritize data products.

• Enhance usability, discoverability, and self-service utilization of analytical data.

• Develop utilities using Python, SQL, shell scripting, and similar technologies to automate data preparation, validation, deployment, monitoring, and operational workflows.

• Create repeatable engineering patterns to replace manual analytics processes.

• Engage in code reviews, debugging, performance optimization, and production support.

• Utilize Git, CI/CD, automated testing, modular development, and infrastructure-aware deployment practices.

• Set standards and design patterns for analytics engineering, modeling, semantic layers, and data products.

• Offer technical guidance and mentorship to analytics engineers, analysts, and related data teams.

• Evaluate architectures and code while remaining an active contributor to the platform.

• Collaborate with data platform and data engineering teams on architecture, performance, governance, and data quality.

• Assist in defining the roadmap for the organization's analytics engineering capabilities.

⛳️ Requirements

• Minimum of 10 years of experience in analytics engineering, data engineering, business intelligence, or related fields.

• Advanced SQL proficiency and extensive experience in designing analytical data models.

• Practical experience with dbt in production settings.

• Hands-on experience with Databricks, including Delta Lake and modern lakehouse architectures.

• Experience in developing analytical solutions utilized through Tableau or similar BI platforms.

• Strong grasp of dimensional modeling, Gold-layer architecture, semantic modeling, metrics, and data governance.

• Experience in constructing reusable data products instead of solely creating individual reports or dashboards.

• Proficiency in Python and scripting/automation techniques.

• Familiarity with Git, CI/CD, testing, code review, and contemporary software development practices.

• Ability to convert ambiguous business requirements into robust technical solutions.

• Comfortable designing enterprise semantic models, writing dbt transformations, debugging Python, optimizing Databricks workloads, and collaborating with business stakeholders.

• No specific educational credentials required.

🏝️ Benefits

• Opportunities for career advancement within the organization.

• A rewarding work environment.

• Chance to contribute to the transformation of healthcare.

• Work across various locations in the US, South America, and India.