EverCommerce - Senior Data Engineer

About EverCommerce At EverCommerce [Nasdaq: EVCM], we are on a mission to digitally transform the service economy with tailored, end-to-end SaaS solutions that simplify and empower the lives of our 725,000+ customers

As a leading service commerce platform, our modern digital and mobile applications create predictable, informed, and convenient experiences between customers and their service professionals in the areas of Home & Field Services, Health Services, and Wellness industries

We are building an extraordinary company and looking for talented, energetic, and motivated people to join our team

You can learn more about our Company, Culture and Values here: https://careers.evercommerce.com/us/en Data is central to how we build products, drive decisions, and unlock innovation

Our data platform supports analytics, real-time insights, and emerging AI-driven capabilities across the EverCommerce ecosystem

Role Overview We are looking for a Senior Data Engineer to design, build, and scale a modern data platform that supports analytics, real-time use cases, and AI-enabled products

This is a high-impact, hands-on role where you will lead the development of robust, scalable data systems, mentor engineers, and partner cross-functionally to deliver trusted, high-quality data

You will also help evolve our platform toward automation and intelligent pipeline development ,leveragingmodern tooling and AI where it creates real efficiency

Responsibilities: Design, build, andoperate scalable batch and streaming data pipelines Lead architecture decisions for Lakehouse-based data platforms Develop and orchestrate workflows using Apache Airflow Build transformations and analytics-ready datasets using DBT Develop andmaintain real-time pipelines using Kafka Leverage Databricks for large-scale data processing and advanced analytics Design andoptimizestorage using Apache Iceberg and Lakehouse architecture Ingest and manage data from diverse sources using tools like Fivetranmanaged data lake Build andmaintaina semantic layer for trusted reporting and self-service analytics Implement data quality frameworks , observability, and automated testing Optimizeperformance, scalability, and cost across AWS services (Athena, EC2, etc.) Partner with BI, product, and engineering teams to deliver actionable data solutions Mentor junior engineers and contribute to engineering best practices and standards Drive improvements in developer productivity and pipeline reliability Skills and Qualifications needed for this role: 7+ years of experience in Data Engineering or related field Strongproficiencyin Python and SQL Deep experience with Apache Airflow and workflow orchestration Expertisein DBT for data transformation and modeling Strong hands-onexperience with Databricks Strong experience building streaming pipelines (Kafka or similar) Strong hands-onexperience with data ingestion tools such as Fivetran Hands-on experience with building automated QA,monitoringandobservabilityfor data lake / lake house Solid understanding of Lakehouse architecture and Apache Iceberg Experience implementing data quality, testing, and observability frameworks Familiarity with AWSecosystem (Athena, EC2, S3, etc.) Strong foundationin data modeling and semantic layer design Proven ability to design scalable systems and influence technical direction Nice tohaves (Including AI Capabilities) Experience enabling AI/GenAI use cases on analytics platforms (e.g., Databricks Genie or similar) Exposure to AI-assisted development tools for: Automating data pipeline generation Accelerating ingestion-to-consumption workflows Automating QA from ingestion to consumption Automation DBT model generation Improving testing, documentation, and lineage tracking Experience building orleveraging metadata-driven or declarative pipelines Familiarity with self-service BI tools (e.g., ThoughtSpot) Knowledge of data governance, cataloging, and lineage systems Experience in SaaS or multi-product ecosystems Under