Senior Data Engineer

### Who you are
- You are passionate about building scalable, reliable data platforms and transforming data into actionable insights that drive product and business decisions. You enjoy working across the full data lifecycle — from designing and maintaining data pipelines and warehouse models to building dashboards and analytics that empower stakeholders
- You have experience working with modern cloud data platforms and enjoy solving complex problems involving large datasets, data modeling, and analytics
- 7+ years of experience in data engineering, analytics engineering, or data platform development
- 7+ years of advanced SQL experience working with large datasets
- 5+ years experience with programming languages such as Python, R, Go, or JavaScript
- 5+ years experience with data transformation frameworks such as dbt core or similar tools
- 5+ years experience leveraging cloud technologies (AWS preferred) for data pipelines, storage, and analytics
- 3+ years experience with modern columnar data warehouses such as Amazon Redshift, Snowflake, or Google BigQuery
- Strong experience designing data models optimized for analytics and reporting
- Experience building BI dashboards using tools such as ThoughtSpot, Looker, Tableau, PowerBI, or similar
- Experience working with data ingestion tools such as Fivetran, AWS DMS, Kafka, Spark, or similar technologies
- Strong understanding of data governance, privacy, and access control
- Ability to translate business questions into data models, metrics, and dashboards
- Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders
- Demonstrated ability to solve complex data problems and deliver scalable solutions

### What the job involves
- EverHealth, a division of EverCommerce, is seeking a Senior Data Engineer to make significant contributions to our EverHealth EHR Product Reporting and Analytics capabilities
- We are seeking a Senior Data Engineer to focus on designing, implementing, maintaining and enhancing our data warehouse and data pipelines (per brand) for the purpose of incorporating in-application operational reporting and analytics into our products
- This role presents an opportunity to work with multiple brands under the Everhealth umbrella, including different technology stacks, customer use cases, and data sources
- Success in this role will drive improved healthcare efficiency and ultimately better patient care
- This role sits at the intersection of data engineering and analytics, owning both the data warehouse infrastructure and the BI layer used by product and business teams
- You will partner closely with product managers, engineers, and business stakeholders to define metrics, model data, and deliver analytics that help teams better understand product performance and operational health
- You are responsible for ensuring that data is reliable, accessible, secure, and actionable for internal teams and customers
- This role will play a key part in shaping our evolving data platform and analytics capabilities. You will have the opportunity to influence data architecture, define core business metrics, and help establish best practices for analytics across the organization
- Design, build, and maintain scalable data pipelines and warehouse infrastructure to support analytics and reporting needs
- Develop and maintain clean, well-modeled datasets optimized for analytics and self-service reporting
- Partner with product managers and stakeholders to define key metrics, reporting requirements, and product analytics needs
- Build and maintain BI dashboards and reports that provide visibility into product performance, operational metrics, and customer behavior
- Ensure data quality, reliability, and governance across the analytics platform
- Integrate and maintain data ingestion pipelines from internal and external systems
- Improve the data warehouse performance and data modeling layer to enable faster and more reliable analytics
- Enable self-service analytics by creating curated datasets and semantic layers for internal teams
- Document datasets, metric definitions, and data lineage to improve data discoverability and trust in data
- Collaborate with engineering teams to ensure data is captured, modeled, and surfaced effectively for analytics use cases
- Data pipeline engineering and warehouse management – 40%
- Data modeling and transformation (analytics layer) – 25%
- BI dashboard and reporting development – 20%
- Stakeholder collaboration and domain knowledge gathering – 10%
- Meetings / presentations / demos – 5%

### Benefits
- Flexibility to work where/how you want – in-office, remote, or hybrid
- Robust health and wellness benefits, including an annual wellness stipend
- Continued investment in your professional development through Udemy
- 401k with company match
- Flexible and generous paid time off
- Employee Stock Purchase Program