Senior Data Engineer Contractor

Senior Data Engineer

Position: Senior Data 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 Data Engineer is responsible for designing building optimizing and supporting reliable data pipelines and cloud data platform services that enable enterprise analytics reporting operational insights and data-driven decision-making. This role focuses on the engineering foundations that move transform govern and deliver trusted data across eBlus modern data ecosystem.

This position requires strong hands-on experience with Azure SQL Google Cloud Platform BigQuery Airbyte Airflow dbt SQL and modern data pipeline patterns. The Senior Data Engineer partners closely with analytics engineers data analysts software engineers product stakeholders and business leaders to ensure data is accurate timely scalable secure and accessible for analytical and operational use cases.

The role balances pipeline engineering execution platform reliability data architecture data quality cost optimization documentation and technical mentorship while helping modernize eBlus data platform and improve confidence in enterprise data assets.

Key Responsibilities

Modern Data Pipeline Engineering

• Design build test deploy and maintain scalable batch and scheduled data pipelines using Airbyte Airflow dbt SQL BigQuery Azure SQL and cloud-native data services.

• Engineer reliable ingestion orchestration transformation validation monitoring alerting and recovery patterns for ELT and ETL workflows.

• Build and maintain source system integrations extraction jobs landing patterns staging structures incremental loads and change data capture approaches where appropriate.

• Develop reusable pipeline frameworks templates and engineering patterns that improve delivery speed maintainability and operational consistency.

• Ensure pipelines are designed for performance resiliency observability scalability cost efficiency and ease of support.

Cloud Data Platform & Warehouse Development

• Design implement and optimize cloud data structures across Google Cloud Platform BigQuery Azure SQL and related data services.

• Develop and maintain raw staged curated and consumption-ready data layers that support analytics engineering business intelligence reporting and downstream operational workflows.

• Partner with architecture and engineering leaders to improve data platform cohesion across application integration and data layers.

• Optimize BigQuery datasets partitioning clustering indexing query performance storage patterns and workload costs.

• Contribute to modernization roadmaps that reduce data platform technical debt and improve scalability maintainability and governance.

Data Transformation Quality & Governance

• Build and support transformation workflows in dbt and SQL including models tests snapshots macros documentation lineage and deployment practices.

• Implement data quality checks reconciliation logic anomaly detection patterns data freshness monitoring and source-to-target validation.

• Partner with analytics engineers and stakeholders to ensure curated datasets are accurate well-documented trusted and aligned to business definitions.

• Promote strong data governance practices including ownership metadata lineage access controls naming standards documentation and data retention awareness.

• Support root cause analysis and remediation for data incidents pipeline failures quality issues and performance bottlenecks.

DevOps Automation & Operational Excellence

• Apply modern engineering practices such as version control peer review automated testing CI/CD environment management release discipline and repeatable deployment processes for data assets.

• Create and maintain operational dashboards job health monitoring runbooks failure response procedures and pipeline support documentation.

• Improve reliability through proactive monitoring alerting backfill strategies retry logic dependency management and incident response practices.

• Collaborate with DevOps platform security and engineering teams to strengthen cloud utilization access management observability resiliency and compliance alignment.

• Evaluate and recommend tools patterns and automations that improve productivity reliability security and cost efficiency across the data platform.

Cross-Functional Partnership & Technical Leadership

• Work closely with analytics engineers product managers engineering teams and business stakeholders to understand data needs and deliver reliable data solutions.

• Translate business and technical requirements into scalable ingestion transformation storage and delivery designs.

• Provide senior-level technical guidance code review troubleshooting support and mentorship to data and analytics team members.

• Communicate technical concepts tradeoffs risks and delivery status clearly to both technical and non-technical audiences.

• Foster a culture of ownership documentation operational discipline continuous improvement and responsible innovation.

Experience Skills & Qualifications

Education

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

• Masters degree or equivalent experience preferred.

Experience

• 5 years of progressive experience in data engineering data platform engineering analytics engineering or a related technical role.

• Strong hands-on experience designing and supporting modern data pipelines ELT/ETL workflows orchestration and cloud data warehouse solutions.

• Deep experience with SQL and relational data concepts including Azure SQL or comparable SQL Server-based platforms.

• Hands-on experience with Google Cloud Platform and BigQuery including dataset design query optimization cost management and operational support.

• Experience with Airbyte or similar data ingestion tools and Airflow or similar workflow orchestration tools.

• Experience with dbt for transformation development testing documentation lineage and model deployment.

• Experience supporting BI and analytics consumption layers such as Looker and Google Data Studio / Looker Studio preferred.

• Experience with CI/CD Git-based workflows automated testing release management and modern DevOps practices for data assets.

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

Skills

• Advanced SQL development performance tuning data modeling and troubleshooting skills.

• Strong understanding of data warehousing dimensional modeling lakehouse concepts data marts data contracts and source-to-target mapping.

• Ability to design reliable observable and scalable pipelines across ingestion staging transformation validation and consumption layers.

• Strong critical thinking problem-solving debugging and root cause analysis capabilities.

• Strong documentation habits including technical specifications runbooks lineage data dictionaries and support procedures.

• Ability to balance delivery speed with engineering quality security compliance reliability and cost efficiency.

• Effective communication skills with the ability to explain complex data engineering concepts to technical and non-technical stakeholders.

• High ownership mindset operational discipline and ability to work independently while collaborating across teams.

• Ability to mentor peers promote standards and contribute to continuous improvement in an evolving data environment.

Preferred Certifications & Tools

• Google Cloud Platform BigQuery or data engineering certifications.

• Microsoft Azure Azure SQL SQL Server or related cloud data certifications.

• Experience with Python or another scripting language for automation data validation or operational tooling.

• Familiarity with Agile/Scrum methodologies and work management tools such as Azure DevOps or similar modern development services.

• Familiarity with data privacy security auditability and compliance expectations in healthcare or regulated environments.

Physical & Technical Environment

• Ability to work at a desk in the office 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.

• Ability to work effectively in remote and hybrid collaboration environments.

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.

CareTria is an Equal Opportunity Employer

CareTria 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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