Team Lead, Data Analytics

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 Team Lead Data Analytics is responsible for the day-to-day leadership technical execution and operational maturity of eBlus data analytics function. This role leads analytics engineers data engineers and data architects in designing building and supporting modern data pipelines analytical data models dashboards and governed reporting solutions across the organization.

This leader ensures the analytics platform evolves with scalable secure and reliable data architecture across Azure SQL Google Cloud Platform BigQuery Airbyte Airflow dbt Looker and Google Data Studio / Looker Studio. The Team Lead balances hands-on technical direction with team coordination stakeholder partnership data quality and delivery discipline to enable trusted business insights and support growth of the platform.

Key Responsibilities

Data Platform Architecture & Technical Execution

• Lead the design development and optimization of analytics solutions across cloud data platforms including Google Cloud Platform and BigQuery.

• Ensure cohesion across source systems ingestion patterns transformation logic semantic models dashboards and downstream business reporting.

• Develop and maintain scalable data models curated datasets and reusable analytical patterns that support operational financial product and customer-facing reporting needs.

• Contribute to platform modernization roadmaps technical standards and build vs. buy recommendations for data tools and services.

• Partner with engineering and platform leaders to reduce data platform technical debt through structured improvements to pipelines models documentation and data contracts.

Modern Data Pipeline Development & Operations

• Oversee the development and support of reliable batch and scheduled data pipelines using Airbyte Airflow dbt SQL and cloud-native services.

• Guide ingestion orchestration transformation testing deployment and monitoring practices for modern ELT and ETL workflows.

• Establish and improve pipeline observability data freshness monitoring failure alerting lineage and recovery processes.

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

• Promote engineering practices such as version control peer review environment management automated testing CI/CD and documentation for data assets.

Analytics Engineering BI & Stakeholder Enablement

• Lead delivery of dashboards reports metrics and analytical products using Looker and Data Studio / Looker Studio.

• Translate business goals and operational questions into clear data requirements metrics definitions models and visualizations.

• Partner with Product Engineering Operations Finance Sales Customer Success and executive stakeholders to prioritize high-value analytics work.

• Define and support semantic models governed metrics reusable LookML assets and self-service reporting patterns that improve business adoption and trust.

• Communicate complex data concepts clearly to technical and non-technical audiences including tradeoffs risks assumptions and recommended next steps.

Team Leadership & Delivery Governance

• Lead mentor and coordinate a team of analytics engineers data engineers and data architects ensuring clear priorities efficient workflow and consistent execution.

• Support sprint planning backlog grooming estimation roadmap sequencing and delivery reporting for analytics initiatives.

• Coach team members on technical design data modeling SQL quality pipeline reliability analytics engineering practices and stakeholder communication.

• Foster a culture of accountability continuous improvement collaboration knowledge sharing and responsible experimentation.

• Establish measurable analytics team health metrics including pipeline reliability dashboard adoption data quality cycle time incident trends and stakeholder satisfaction.

Data Governance Quality Security & Compliance

• Implement data governance standards that improve data quality integrity usability ownership and documentation across analytics assets.

• Define and enforce testing practices for dbt models transformation logic data reconciliation and key business metrics.

• Partner with security compliance engineering and business owners to support appropriate access controls privacy expectations and regulated-environment requirements.

• Maintain clear documentation for logical and physical data models source mappings lineage refresh schedules dashboard definitions and known limitations.

• Ensure analytics practices align with organizational standards for secure compliant and reliable SaaS operations.

Cloud Cost Optimization & Future-Focused Analytics

• Monitor and optimize data platform performance storage compute usage query efficiency and cloud costs across BigQuery GCP and related data services.

• Evaluate emerging technologies and practices that improve scalability reliability automation productivity and business insight generation.

• Identify opportunities to use AI-enabled or automated approaches for data quality checks documentation pipeline support and analytics development while maintaining responsible governance.

• Stay current on industry trends in modern data stacks healthcare analytics cloud data warehousing orchestration analytics engineering and BI enablement.

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 data analytics analytics engineering data engineering BI engineering or a related technical discipline.

• 2 years of experience leading mentoring or managing technical team members in a delivery-oriented environment.

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

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

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

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

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

• Strong SQL skills including performance tuning complex transformations analytical modeling and data validation.

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

• Strong architectural instincts for modern cloud data platforms pipeline reliability data modeling and reporting scalability.

• Excellent communication skills with the ability to explain complex data concepts to executives business stakeholders and technical teams.

• Proven ability to balance hands-on technical execution with team leadership prioritization and delivery governance.

• Strong critical thinking diligence problem-solving and operational discipline.

• Collaborative leadership style with high emotional intelligence and the ability to drive change in evolving SaaS environments.

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 C# or other programming languages used for automation data processing or analytics engineering support.

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

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.

Equal Opportunity Employer

eBlu Solutions is an Equal Opportunity Employer. eBlu Solutions seeks talent from all backgrounds to bring diversity of thought agility and capability to our organization. We promote a working environment where all employees are treated and rewarded fairly. We do not tolerate any form of discrimination that adversely affects individuals or groups based on national origin race color religion sex gender sexual orientation marital status disability age or any other legally protected aspect of a persons identity.

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