Remote Data Engineer

Summary

Join Demyst, a leading data management company, as a Lead Engineer with a strong data engineering focus to deliver our next-generation data platform to leading enterprises across North America. In this role, you will lead a team of data engineers, oversee the development and management of data pipelines, and contribute hands-on to coding, architectural decisions, and data engineering strategy.

Requirements

• Bachelor's degree or higher in Computer Science, Data Engineering, or related fields
• 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

Responsibilities

• 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

Benefits

• Distributed team and culture, with fully flexible working hours and location
• Collaborative, inclusive, and dynamic culture
• Generous benefits and compensation plans
• ESOP awards available for tenured staff