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.

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.