Lead Data Engineer, Demyst

• Bachelor's degree or higher in Computer Science, Data Engineering, or related fields. Equivalent work experience is also highly valued
• 5-10 years of experience in data engineering, software engineering, or client deployment roles, with at least 3 years in a leadership capacity
• Strong leadership skills, including the ability to mentor and motivate a team, lead through change, and drive outcomes
• Expertise in designing, building, and optimizing ETL/ELT data pipelines using Python, JavaScript, Golang, Scala, or similar languages
• Experience in managing large-scale data processing environments, including Databricks and Spark
• Proven experience with Apache Airflow to orchestrate data pipelines and manage workflow automation
• Deep knowledge of cloud services, particularly AWS (EC2/ECS, Lambda, S3), and their role in data engineering
• Hands-on experience with both SQL and NoSQL databases, with a deep understanding of data modeling and architecture
• Strong ability to collaborate with clients and cross-functional teams, delivering technical solutions that meet business needs
• Proven experience in unit testing, integration testing, and engineering best practices to ensure high-quality code
• Familiarity with agile project management tools (JIRA, Confluence, etc.) and methodologies
• Experience with data visualization and analytics tools such as Jupyter Lab, Metabase, Tableau
• Strong communicator and problem solver, comfortable working in distributed teams

• Demyst is seeking a Lead Engineer with a strong data engineering focus to play a pivotal role in delivering our next-generation data platform to leading enterprises across North America
• In this role, you will lead a team of data engineers with a primary focus on data integration and solution deployment
• You will oversee the development and management of data pipelines, ensuring they are robust, scalable, and reliable
• This is an ideal opportunity for a hands-on data engineering leader to apply technical, leadership, and problem-solving skills to deliver high-quality solutions for our clients
• Your role will involve not only technical leadership and mentoring but also actively contributing to coding, architectural decisions, and data engineering strategy
• You will guide your team through complex client deployments, from planning to execution, ensuring that data solutions are effectively integrated and aligned with client goals
• Demyst is a remote-first company
• The candidate must be based in the United States
• Lead the configuration, deployment, and maintenance of data solutions on the Demyst platform to support client use cases
• Supervise and mentor the local and distributed data engineering team, ensuring best practices in data architecture, pipeline development, and deployment
• Recruit, train, and evaluate technical talent, fostering a high-performing, collaborative team culture
• Contribute hands-on to coding, code reviews, and technical decision-making, ensuring scalability and performance
• Design, build, and optimize data pipelines, leveraging tools like Apache Airflow, to automate workflows and manage large datasets effectively
• Work closely with clients to advise on data engineering best practices, including data cleansing, transformation, and storage strategies
• Implement solutions for data ingestion from various sources, ensuring the consistency, accuracy, and availability of data
• Lead critical client projects, managing engineering resources, project timelines, and client engagement
• Provide technical guidance and support for complex enterprise data integrations with third-party systems (e.g., AI platforms, data providers, decision engines)
• Ensure compliance with data governance and security protocols when handling sensitive client data
• Develop and maintain documentation for solutions and business processes related to data engineering workflows
• Other duties as required

• Work with the largest consumer and business external data market in an emerging industry that is fueling AI globally
• Have an impact in a scaling but small team offering real autonomy and responsibility for client outcomes
• Stretch yourself to help define and support something entirely new that will impact billions
• Work within a strong, tight-knit team of subject matter experts
• Small enough where you matter, big enough to have the support to deliver what you promise
• Distributed working team and culture, recognition of outcomes and merit, not presenteeism
• Generous benefits

Total funding: $24.5m

The power of external data is a hot topic, particularly for financial institutions and insurers who must stay compliant as they roll out new products. However, with the data landscape becoming increasingly fragmented, deploying external data at scale has become a significant challenge.