Senior Data Engineer

🕒 May 21

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Logo of EverCommerce

EverCommerce

1001 - 5000 employees

Founded 2016

☁️ SaaS

🤝 B2B

🛍️ eCommerce

💰 Private Equity Round on 2019-07

SaaS • B2B • eCommerce

EverCommerce is the leading service commerce platform, providing vertically-tailored, integrated SaaS solutions to over 500,000 global service-based businesses. Established in 2016, EverCommerce offers software solutions that help businesses market their services, streamline day-to-day operations, and enhance customer engagement. The company specializes in powering the service economy with digital transformation across multiple industries, including Home & Field Services, Health Services, and Fitness & Wellness. EverCommerce's technology aims to accelerate growth, improve operations, and increase retention for small and medium-sized businesses, transforming the way they interact with customers through modern digital and mobile applications.

📋 Description

• 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.

🏖️ 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.

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