EverCommerce - Senior Data Engineer

EverCommerce is on a mission to digitally transform the service economy with tailored SaaS solutions. They are seeking a Senior Data Engineer to design, build, and scale a modern data platform that supports analytics and AI-enabled products while leading the development of robust data systems and mentoring engineers.

Responsibilities:

• Design, build, and operate 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 and maintain real-time pipelines using Kafka
• Leverage Databricks for large-scale data processing and advanced analytics
• Design and optimize storage using Apache Iceberg and Lakehouse architecture
• Ingest and manage data from diverse sources using tools like Fivetran managed data lake
• Build and maintain a semantic layer for trusted reporting and self-service analytics
• Implement data quality frameworks, observability, and automated testing
• Optimize performance, 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

Requirements:

• 7+ years of experience in Data Engineering or related field
• Strong proficiency in Python and SQL
• Deep experience with Apache Airflow and workflow orchestration
• Expertise in DBT for data transformation and modeling
• Strong hands-on experience with Databricks
• Strong experience building streaming pipelines (Kafka or similar)
• Strong hands-on experience with data ingestion tools such as Fivetran
• Hands-on experience with building automated QA, monitoring and observability for data lake / lake house
• Solid understanding of Lakehouse architecture and Apache Iceberg
• Experience implementing data quality, testing, and observability frameworks
• Familiarity with AWS ecosystem (Athena, EC2, S3, etc.)
• Strong foundation in data modeling and semantic layer design
• Proven ability to design scalable systems and influence technical direction
• 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 or leveraging 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
• Understanding of privacy, compliance, and secure data access patterns