Senior Analytics Engineer

Senior Analytics Engineer

Position: Senior Analytics Engineer

Location: Louisville Kentucky (Remote Hybrid)

FLSA Status: Exempt

eBlu Solutions a CareTria Company was founded in 2012 to help specialty medical practices manage the complex workflow associated with high-cost infusion and injection treatments. Simply put our solution gets patients to treatment faster.

Job Summary

The Senior Analytics Engineer is responsible for designing developing and supporting trusted analytical data models modern data pipelines and business intelligence assets that enable high-quality reporting and decision-making across CareTria Patient Access Solutions. This role serves as a senior technical contributor within the Data Analytics function partnering closely with analytics engineers data engineers data architects product teams engineering teams and business stakeholders.

This position requires strong hands-on experience with Azure SQL Google Cloud Platform BigQuery Airbyte Airflow dbt Looker and Google Data Studio / Looker Studio. The Senior Analytics Engineer will translate business needs into scalable data models governed metrics reliable ELT/ETL workflows and well-documented analytics solutions that support operational financial product customer and executive reporting needs.

The role balances analytics engineering execution data quality ownership stakeholder enablement and technical mentorship while helping modernize eBlus data platform and improve confidence in enterprise data assets.

Key Responsibilities

Analytics Engineering & Data Modeling

• Design build test and maintain curated analytical datasets dimensional models semantic models and reusable data assets using SQL dbt BigQuery Azure SQL and related cloud data services.

• Translate business requirements into clear metrics definitions transformation logic source mappings and scalable data models that support accurate reporting and self-service analytics.

• Develop and maintain dbt models tests documentation lineage macros and reusable analytics engineering patterns.

• Optimize SQL BigQuery queries Azure SQL extracts and transformation workflows for performance reliability maintainability and cost efficiency.

• Ensure source-to-report traceability across operational systems Azure SQL GCP BigQuery dbt models Looker and Data Studio / Looker Studio assets.

Modern Data Pipeline Development & Operations

• Build enhance and support modern batch and scheduled data pipelines using Airbyte Airflow dbt SQL and cloud-native data services.

• Develop ingestion orchestration transformation testing deployment monitoring and recovery practices for reliable ELT and ETL workflows.

• Partner with data engineering and platform teams to integrate source systems improve data freshness and reduce manual reporting processes.

• Implement pipeline observability data quality checks freshness monitoring failure alerting and operational documentation.

• Support CI/CD version control peer review environment management and release practices for data models and pipeline code.

Business Intelligence & Stakeholder Enablement

• Design build and support dashboards reports governed metrics and analytical products using Looker and Google Data Studio / Looker Studio.

• Partner with Product Engineering Operations Finance Sales Customer Success and leadership stakeholders to understand analytical needs and deliver actionable insights.

• Define and support semantic models LookML assets dashboard standards and self-service reporting patterns that improve usability and trust.

• Communicate data definitions assumptions limitations tradeoffs and recommendations clearly to both technical and non-technical audiences.

• Help stakeholders interpret data trends investigate discrepancies and improve data-driven decision-making.

Data Quality Governance & Documentation

• Own data quality practices for assigned subject areas including validation rules reconciliation checks automated tests issue triage and root-cause analysis.

• Document logical and physical data models metric definitions source mappings transformation logic lineage refresh schedules and known limitations.

• Contribute to data governance standards that improve data quality integrity ownership usability privacy and access control.

• Partner with security compliance engineering and business owners to ensure analytics assets align with regulated-environment expectations and organizational standards.

• Promote consistent naming conventions development standards documentation practices and review processes across analytics assets.

Technical Leadership & Continuous Improvement

• Serve as a senior technical resource for analytics engineering design SQL quality dbt best practices modeling decisions dashboard development and pipeline reliability.

• Mentor analytics engineers and analysts through code reviews design guidance documentation standards and practical knowledge sharing.

• Contribute to analytics platform modernization roadmaps technical standards backlog refinement estimation and delivery planning.

• Identify opportunities to reduce technical debt automate recurring analytics work improve pipeline resiliency and increase stakeholder confidence in data products.

• Stay current on modern data stack practices cloud data warehousing healthcare analytics analytics engineering orchestration BI tools and responsible AI-enabled automation opportunities.

Experience Skills & Qualifications

Education

• Bachelors degree in Computer Science Data Science Information Systems Statistics Engineering or a related technical field required.

• Masters degree equivalent experience or relevant professional certifications preferred.

Experience

• 5 years of progressive experience in analytics engineering data engineering BI engineering data analytics or a related technical discipline.

• Hands-on experience with Google Cloud Platform and BigQuery including analytical warehouse design query optimization data modeling and cost-aware development.

• Experience with Azure SQL or Microsoft SQL Server environments and integration with cloud analytics platforms.

• Practical experience building and supporting modern data pipelines using Airbyte Airflow dbt SQL and cloud-native data services.

• Experience developing BI and reporting solutions in Looker and Google Data Studio / Looker Studio.

• Strong understanding of data warehousing dimensional modeling semantic modeling ETL/ELT orchestration data governance data quality and analytics lifecycle practices.

• Experience with Agile/Scrum SDLC practices version control peer review CI/CD and Azure DevOps or similar modern development platforms.

• Experience in healthcare regulated environments SaaS platforms specialty pharmacy or complex workflow systems preferred.

Skills

• Advanced SQL skills including complex transformations performance tuning analytical modeling validation and troubleshooting.

• Strong dbt development skills including model organization tests documentation lineage macros and deployment practices.

• Strong working knowledge of BigQuery GCP data services Azure SQL Airbyte Airflow Looker and Data Studio / Looker Studio.

• Ability to translate business objectives into technical data designs governed metrics and actionable analytics deliverables.

• Strong analytical thinking problem-solving diligence and ability to investigate complex data issues from source system through dashboard.

• Clear communication skills with the ability to explain technical data concepts to business stakeholders executives and engineering partners.

• Ability to work independently manage multiple priorities and deliver high-quality data products in a collaborative delivery-oriented environment.

• Commitment to data quality maintainability documentation operational discipline and continuous improvement.

Preferred Certifications & Technical Exposure

• Google Cloud certifications related to data engineering cloud architecture or analytics.

• dbt Looker BigQuery Azure or data engineering certifications or equivalent hands-on experience.

• Familiarity with Python Java or other programming languages used for automation data processing or analytics engineering support.

• Experience with data cataloging lineage observability metadata management automated data quality platforms or data contract practices.

• Experience with healthcare data claims benefits verification prior authorization specialty pharmacy patient access or complex operational workflows.

Physical & Technical Environment

• Ability to work at a desk in the office or remote environment for long periods of time.

• The noise level in the work environment is moderate.

• Specific vision abilities required by this job include close vision and color vision.

• Ability to maintain focus under high levels of pressure and multiple priorities.

Benefits

• Competitive pay and performance-based incentives.

• Comprehensive health dental and vision insurance.

• Retirement savings plan with company matching.

• Flexible schedules with both remote and hybrid work options.

• Professional development and growth opportunities.

• Generous paid time off and holiday schedule.