This range is provided by Stackless. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range Stackless is a leading data solutions provider, partnering with businesses to tackle their most complex data challenges and maximize their opportunities. We specialize in cutting-edge data products that can seamlessly augment or replace our customers’ existing data stacks. Our mission is to deliver integrated, high-performance data solutions through leading-edge engineering, automation, and system design. About the Role We are seeking a full-time contract Senior Data Engineer to join our new Customer Success team. This role is critical in ensuring our customers have a seamless experience with Stackless, resolving technical issues, optimizing implementations, and advocating for product improvements. As a key member of the team, you will troubleshoot customer data issues, improve ETL pipelines, and collaborate with our Product team to enhance our platform. NOTE: This is a very technical SENIOR role. Please do not apply if you do not meet the minimum requirements below. What You'll Do Serve as a technical resource, responding to customer support tickets and ensuring timely issue resolution. Diagnose and troubleshoot data pipeline issues, ETL failures, and data integrity concerns. Collaborate with customers to optimize their Stackless implementation and ensure their data workflows are efficient, scalable, and reliable. Work closely with the Product team to provide insights and recommendations on product enhancements based on customer feedback and recurring challenges. Develop, maintain, and optimize ETL pipelines using tools like DBT, Fivetran, and Airflow. Design and implement data quality checks to ensure data accuracy and consistency across platforms. Improve internal monitoring and alerting to proactively detect and resolve customer issues. Assist in writing customer-facing documentation and knowledge base articles to enhance self-service support. Maintain and enhance the performance of our data solutions by optimizing queries, models, and infrastructure. Ensure that we meet our Service Level Agreements (SLAs) regarding uptime, response times, and resolution targets. Requirements Fluency in English 5+ years of experience in data engineering, with a focus on ETL development, data modeling, and performance optimization. Proficiency in Python, SQL, and Snowflake with experience developing, debugging, and optimizing complex queries. Hands-on experience with DBT (6+ months required) and familiarity with data transformation frameworks. Working knowledge of one or more modern data stack tools, such as Redshift, Looker, Metabase, Tableau, Fivetran, Databricks, Stitch, Sigma, Delta Lake, or Airflow. Strong understanding of data pipeline design and best practices for scalability and reliability. Ability to analyze and troubleshoot large datasets and resolve data integrity issues. Excellent problem-solving skills and a customer-centric approach to technical support. Strong communication skills, with the ability to explain technical concepts to non-technical users and write clear documentation. Self-motivated and able to work independently in a fast-paced, remote-first environment. Bonus Points Experience working in a customer-facing engineering role (support, solutions engineering, or professional services). Previous experience with data observability and monitoring tools to proactively identify and resolve issues. Exposure to cloud-based data architectures (AWS, GCP, Azure). Experience automating operational tasks and improving support workflows. Why Join Stackless? Remote-first culture – work from anywhere. Collaborative and innovative environment where your ideas matter. Opportunities for career growth, technical leadership, and product influence. Competitive salary and benefits package. Work with cutting-edge data technologies in a fast-growing company. Ready to Join Us? Apply today and help us build a world-class customer success experience. Seniority level Mid-Senior level Employment type Full-time Job function Information Technology Industries Data Infrastructure and Analytics #J-18808-Ljbffr