Senior Data Engineer

About Ever Commerce

At Ever Commerce [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.

You can learn more about our Company, Culture and Values here:

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.

• 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

• 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., Thought Spot)
• Knowledge of data governance, cataloging, and lineage systems
• Experience in SaaS or multi‑product ecosystems
• Understanding of privacy, compliance, and secure data access patterns

This is a fully remote, U.S. based position with minimal to no travel required. You may be asked to travel up to 4 times per year for quarterly planning. The Ever Commerce 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…