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, leveraging modern tooling and AI where it creates real efficiency.

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

Skills and Qualifications needed for this role:

• 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 (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 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

Where

This is a fully remote, US based position with minimal to no travel required. You may be asked to travel up to 4 times per year for quarterly planning. The EverCommerce team is distributed globally, with teams in the U.S., Canada, the U.K., Jordan, New Zealand, and Australia. With a widely distributed team, we are used to working remotely across different time zones. This role can be based anywhere in the United States or Canada - if you're close to one of our offices, we can set you up in-office or you can work 100% remotely. Please note that you must be eligible to work without sponsorship to qualify for this position, and this role may require travel to our Corporate Headquarters in Denver, Colorado, or to other office locations around North America.

Benefits and Perks

• 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.

Compensation: The target base compensation for this position is $130,000 to $150,000 USD per year in most US locations. Final offer amounts are determined by multiple factors including location, local market variances, and candidate experience and expertise, and may vary from the amounts listed above.