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Lead data architects at Thoughtworks play a key part in developing modern data architecture approaches to meet business objectives and provide end-to-end data solutions. They take a technical leadership role in enabling clients and Thoughtworks teams to align on outcomes that support the vision painted by data strategists. They lead, with support, the design and architecture of initiatives which are key to the delivery of solutions to budget and timelines. They also guide and mentor delivery teams on architectural decisions to deliver to the solution agreements.
Job Responsibility:
Navigate, with support, a data project's architectural concerns, enabling delivery teams to deliver on accepted standards within time and budget
Provide client-facing technical leadership and guidance on topics related to data architecture, engineering, and analytics to advise clients on bringing their data strategy to life
Interact with client counterparts from the enterprise architecture group to deliver, share, align and sign-off on key architectural decisions, trade-offs and ways of working
Communicate both high-level and low-level technical details of data architecture to engineers and business stakeholders
Understand and can collaborate at the intersection of analytical and operational architectures
Lead with support the technical design of data governance, data security and data privacy to fulfill compliance requirements
Lead, with support, the incorporating of data quality frameworks and processes to address and fulfill requirements as set out in strategy and acceptance criteria
Collaborate with sales and pre-sales to clarify requirements and design viable solutions
Requirements:
Experience in defining and implementing different types of data architecture, analyzing trade-offs and can define technology stacks for different types of data architecture
Exposure to designing application system architecture based on big data, artificial intelligence and related technologies
Experience in building, maintaining and tuning data platforms, as well as experience in data warehouse design, data modeling, data monitoring and maintenance
Experience with common design patterns, application frameworks and foundational/theoretical knowledge (i.e.: distributed systems, data intensive applications, etc.)
Proficient in common open-source distributed computing/storage technologies, including but not limited to YARN, Impala, Spark, MapReduce, Kafka and Flink, with practical project architecture experience
Good understanding of business and communication, collaboration skills, strong learning and summarizing abilities
Exposure to defining, developing and enabling data-driven techniques, advanced analytics, ML/AI and data mining applications in enterprise. This includes technologies such as LLMs, VLMs, vector & graph databases and/or agentic architectures
Exposure to developing real-time and low-latency data streaming solutions
Exposure to productionizing machine learning models and applying techniques, tools and processes
Passionate about data infrastructure and operations, with expertise working in cloud environments
Experience influencing others and always advocate for technical excellence while being open to change when needed
Bridge product and technology by helping to translate business needs to software requirements
Ability to develop and execute a technical vision with a focus on business value
Act as a mentor for less experienced peers through both your technical knowledge and ability to inspire a team to deliver extraordinary impact together
Resilient in ambiguous situations and can approach challenges from multiple perspectives