Remote Lead Data Engineer

Description:

• Lead and manage data engineering projects from inception to completion, including goal-setting, scope definition, and ensuring on-time delivery with cross-team collaboration.
• Collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality.
• Design, develop, and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions.
• Create, design, and develop intricate data processing pipelines, addressing clients' most challenging problems.
• Collaborate with data scientists to design scalable implementations of their models.
• Write clean and iterative code based on Test-Driven Development (TDD) and leverage various continuous delivery practices to deploy, support, and operate data pipelines.
• Lead and advise clients on how to use different distributed storage and computing technologies from the plethora of options available.
• Develop data models by selecting from a variety of modeling techniques and implementing the chosen data model using the appropriate technology stack.
• Responsible for data governance, data security, and data privacy to support business and compliance requirements.
• Define the strategy for and incorporate data quality into day-to-day work.

Requirements:

• Experience in leading the system design and implementation of technical solutions is required.
• A passion for working with data; experience in creating Big Data architecture, building and operating data pipelines, and maintaining data storage within distributed systems is essential.
• A deep understanding of data modeling and experience with modern data engineering tools and platforms is necessary.
• Proficiency in writing clean, high-quality code using the preferred programming language is required.
• Experience in building and deploying large-scale data pipelines and data-centric applications using distributed storage and processing platforms in a production setting is essential.
• Familiarity with data visualization techniques and the ability to communicate insights effectively to various audiences is required.
• Experience with data-driven approaches and the ability to apply data security and privacy strategies to solve business problems is necessary.
• Proficiency with different types of databases (e.g., SQL, NoSQL, data lakes, data schemas) is required.

Benefits:

• There is no one-size-fits-all career path at Thoughtworks; employees have the autonomy to develop their careers as they see fit, supported by interactive tools and numerous development programs.
• The company values a cultivation culture that empowers employees in their career journeys and encourages mutual support among teammates.
• Thoughtworks offers a collaborative environment where diverse professionals can learn from and challenge each other, fostering personal and professional growth.