EverCommerce - Senior Data Engineer

EverCommerce

1d • Remote

About The Position

Data is central to how EverCommerce builds products, drives decisions, and unlocks innovation. Our data platform supports analytics, real-time insights, and emerging AI-driven capabilities across the EverCommerce ecosystem. 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, leveraging modern tooling and AI where it creates real efficiency.

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

Nice To Haves

• 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

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

Benefits

• Flexibility to work where/how you want within your country of employment – in-office, remote, or hybrid
• Continued investment in your professional development
• Day 1 access to a robust health and wellness benefits package, including an annual wellness stipend.
• 401k with up to a 4% match and immediate vesting
• Flexible and generous (FTO) time-off
• Employee Stock Purchase Program.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed