Top Benefits
Remote or hybrid work flexibility
Health and wellness benefits with wellness stipend
Professional development via Udemy
About the role
Who you are
- 5+ years experience in a Data Engineering position
- Strong experience with Python and SQL
- Hands-on experience with Apache Airflow5
- Experience working with Databricks
- Expertise using DBT for transformations and analytics modeling
- Experience building streaming data pipelines with Kafka
- Experience with data ingestion tools such as Fivetran
- Working knowledge of Apache Iceberg and modern Lakehouse architectures
- Experience implementing data quality checks, testing frameworks, and pipeline observability
- Familiarity with AWS services including Athena, EC2, and cloud-based data platforms
- Strong understanding of data modeling, analytics, and semantic layer design
- Experience enabling AI or GenAI use cases on top of analytics platforms (e.g., Databricks Genie)
- Experience delivering self-service BI solutions (e.g., ThoughtSpot)
- Knowledge of data governance, metadata management, and data catalogs
- Experience supporting SaaS or multi-product platforms
- Familiarity with privacy, compliance, and secure data access patterns
What the job involves
- We are seeking a Data Engineer II to help design and scale our modern data platform, supporting analytics, self-service BI, real-time use cases, and AI-powered insights
- You’ll work closely with analytics engineers, product teams, and business stakeholders to deliver reliable, high-quality data that drives measurable business outcomes
- This role is hands-on and impact-focused, ideal for someone who enjoys building Lakehouse-based platforms, enabling streaming data, and supporting AI and GenAI use cases in production
- Design, build, and operate scalable batch and streaming data pipelines
- Develop and orchestrate workflows using Apache Airflow
- Implement transformations and analytics-ready datasets using DBT
- Build and maintain real-time pipelines using Kafka
- Leverage Databricks for data processing, analytics, and AI enablement
- Support AI and GenAI use cases, including enabling high-quality data access for tools like Databricks Genie
- Design and optimize data storage using Apache Iceberg and Lakehouse architecture
- Ingest and manage data from diverse internal and external sources using Fivetran
- Handle a wide variety of data structures (structured, semi-structured, and event-based data)
- Build and maintain a semantic layer that enables trusted reporting and self-service analytics
- Implement data quality frameworks, monitoring, and unit test automation to ensure reliability at scale
- Partner with BI, product, and engineering teams to deliver data that is intuitive, trusted, and actionable
- Optimize performance, scalability, and cost across AWS services such as Athena, EC2, and related tooling
- Contribute to data platform standards, documentation, and best practices
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
About EverCommerce
Software Development
1001-5000
EverCommerce is a leading service commerce platform, providing vertically-tailored, integrated SaaS solutions that help more than 690,000 global service-based businesses accelerate growth, streamline operations, and increase retention. Its modern digital and mobile applications create predictable, informed, and convenient experiences between customers and their service professionals. Specializing in Home & Field Services, Health Services, and Fitness & Wellness industries, EverCommerce solutions include end-to-end business management software, integrated payment acceptance, marketing technology, and customer engagement applications.
Top Benefits
Remote or hybrid work flexibility
Health and wellness benefits with wellness stipend
Professional development via Udemy
About the role
Who you are
- 5+ years experience in a Data Engineering position
- Strong experience with Python and SQL
- Hands-on experience with Apache Airflow5
- Experience working with Databricks
- Expertise using DBT for transformations and analytics modeling
- Experience building streaming data pipelines with Kafka
- Experience with data ingestion tools such as Fivetran
- Working knowledge of Apache Iceberg and modern Lakehouse architectures
- Experience implementing data quality checks, testing frameworks, and pipeline observability
- Familiarity with AWS services including Athena, EC2, and cloud-based data platforms
- Strong understanding of data modeling, analytics, and semantic layer design
- Experience enabling AI or GenAI use cases on top of analytics platforms (e.g., Databricks Genie)
- Experience delivering self-service BI solutions (e.g., ThoughtSpot)
- Knowledge of data governance, metadata management, and data catalogs
- Experience supporting SaaS or multi-product platforms
- Familiarity with privacy, compliance, and secure data access patterns
What the job involves
- We are seeking a Data Engineer II to help design and scale our modern data platform, supporting analytics, self-service BI, real-time use cases, and AI-powered insights
- You’ll work closely with analytics engineers, product teams, and business stakeholders to deliver reliable, high-quality data that drives measurable business outcomes
- This role is hands-on and impact-focused, ideal for someone who enjoys building Lakehouse-based platforms, enabling streaming data, and supporting AI and GenAI use cases in production
- Design, build, and operate scalable batch and streaming data pipelines
- Develop and orchestrate workflows using Apache Airflow
- Implement transformations and analytics-ready datasets using DBT
- Build and maintain real-time pipelines using Kafka
- Leverage Databricks for data processing, analytics, and AI enablement
- Support AI and GenAI use cases, including enabling high-quality data access for tools like Databricks Genie
- Design and optimize data storage using Apache Iceberg and Lakehouse architecture
- Ingest and manage data from diverse internal and external sources using Fivetran
- Handle a wide variety of data structures (structured, semi-structured, and event-based data)
- Build and maintain a semantic layer that enables trusted reporting and self-service analytics
- Implement data quality frameworks, monitoring, and unit test automation to ensure reliability at scale
- Partner with BI, product, and engineering teams to deliver data that is intuitive, trusted, and actionable
- Optimize performance, scalability, and cost across AWS services such as Athena, EC2, and related tooling
- Contribute to data platform standards, documentation, and best practices
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
About EverCommerce
Software Development
1001-5000
EverCommerce is a leading service commerce platform, providing vertically-tailored, integrated SaaS solutions that help more than 690,000 global service-based businesses accelerate growth, streamline operations, and increase retention. Its modern digital and mobile applications create predictable, informed, and convenient experiences between customers and their service professionals. Specializing in Home & Field Services, Health Services, and Fitness & Wellness industries, EverCommerce solutions include end-to-end business management software, integrated payment acceptance, marketing technology, and customer engagement applications.