Veritas Veterinary Partners is a premier specialty and emergency veterinary service provider with a presence in NY, NJ, CO, NV and CA. The company is backed by Percheron Capital, a private equity firm with a track record of supporting exceptional teams to accelerate growth and build market-leading companies. Veritas and Percheron both are deeply dedicated to leveraging data to drive strategic decisions and enhance business outcomes. We’re seeking a skilled Data Engineer to join our dynamic team and play a pivotal role in transforming our data into actionable insights.
The Data Engineer will be responsible for designing, building, and optimizing data pipelines and models to support analytics and business intelligence efforts. This role includes developing ETL processes, integrating APIs, and ensuring data models are scalable and high performing for reporting tools like Power BI and Tableau. You will work with data and integration tools from a variety of sources, including veterinary practice management, financial, payroll and ATS systems and utilize technology tools and platforms from Snowflake, SQL Server, Azure SQL, hosted MySQL on AWS, SSIS and Azure Data Factory. Your work will support business intelligence solutions and ensure data is accessible for analysis by various stakeholders.
Key Responsibilities:
- Data Architecture & Modeling
- Design and implement scalable, flexible data marts, data warehouses and data models for analytics and reporting purposes.
- Model and structure data for effective reporting and business intelligence use cases, focusing on Snowflake, MySQL and SQL databases and visualization and reporting tools from Microsoft and Tableau.
- Ensure the data architecture can integrate seamlessly with business applications through integration components, cloud data connectors and API calls.
- Data Engineering:
- Develop and manage ETL/ELT pipelines using tools like SQL Server Integration Services (SSIS) or Azure Data Factory and other third-party ETL platforms.
- Extract, transform, and load data from disparate systems into a centralized data warehouse.
- Optimize data flows and processing for performance, reliability, and scalability.
- Ensure data pipelines can handle both structured and semi-structured data from various sources.
- Integration & Data Management:
- Leverage data connectors & APIs to extract and feed data into databases or BI systems.
- Manage and optimize database performance to ensure data integrity and fast query performance.
- Troubleshoot issues related to data integration, extraction, and transformation.
- Data Visualization and Reporting:
- Familiarity with preparing data for and using data visualization tools such as Power BI.
- Ensure that the data architecture and data models support self-service analytics and is accessible for non-technical business users.
- Partner with BI Analyst to automate data feeds behind interactive dashboards and reports.
- Collaboration and Communication:
- Work closely with business analysts, field operators, senior leadership and other stakeholders to understand data needs and provide relevant solutions.
- Present technical topics in a clear and understandable way.
- Optimization and Maintenance:
- Monitor and optimize data pipelines for performance and efficiency.
- Troubleshoot and resolve issues related to data extraction, transformation, and processing of data.
- Documentation and Best Practices:
- Document data processes, workflows, and reporting solutions for transparency and knowledge sharing.
- Stay updated with industry best practices and emerging technologies to continuously improve data engineering practices
- Continuously explore modern data tools and methodologies, incorporating industry trends to enhance the data strategy.
Qualifications:
- Bachelor’s or master’s degree in computer science, Information Systems, or a related field.
- 7+ years of experience in data engineering, ETL processes, and data pipeline development.
- Proven experience with SQL, MySQL, PostgreSQL, NoSQL and advanced query writing (T-SQL).
- Expertise in SQL Server, MySQL (AWS-hosted), Snowflake, Azure SQL, and Azure Data Factory.
- Experience designing and implementing data models (e.g., star schema, dimensional models) for analytics.
- Familiarity with APIs, data integration techniques and managing structured and semi-structured data.
- Experience with reporting and visualization tools such as Power BI and understanding how to structure data to meet BI needs.
- Proven ability to work with data from HR, ATS and ERP and Financial platforms.
- Experience designing and implementing data models (e.g., star schema, dimensional models) for analytics and BI.
- Hands-on experience developing and managing ETL processes using SSIS or similar tools.
- Strong problem-solving skills with the ability to communicate complex technical concepts to non-technical stakeholders.
Preferred Skills:
- Experience with cloud-based ETL tools like Azure Data Factory.
- Familiarity with data pipeline tools (e.g., dbt, Stitch, Fivetran).
- Knowledge of data governance and security best practices.
Why Join Us:
- Opportunity to build and support a scalable data infrastructure for a high-growth business leveraging innovative data solutions.
- Collaborative and inclusive work environment.
- Competitive salary and benefits package.
- Professional development and career growth opportunities.
Veritas Veterinary Partners is an equal opportunity employer. In accordance with the requirements of all applicable federal, state and local laws, we welcome and encourage diversity in the workplace regardless of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status or any other legally protected status.
Applicants must be authorized to work in the U.S. Veritas does not currently sponsor applicants for work Visas, except for TN or E-3 Visa.
All current positions require the ability to speak, read, and write English proficiently. Additional fluency in other languages is preferred but not required.
United States
