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 responsibilities - You will navigate, with support, a data project's architectural concerns, enabling delivery teams to deliver on accepted standards within time and budget. - You will 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. - You will 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. - You will communicate both high-level and low-level technical details of data architecture to engineers and business stakeholders. - You understand and can collaborate at the intersection of analytical and operational architectures. - You will lead with support the technical design of data governance, data security and data privacy to fulfill compliance requirements. - You will lead, with support, the incorporating of data quality frameworks and processes to address and fulfill requirements as set out in strategy and acceptance criteria. - You will collaborate with sales and pre-sales to clarify requirements and design viable solutions. - Designs the holistic data architecture, governance frameworks, and compliance protocols (PII, Audit Trail). Data Modeling, AWS Data Services (e.g., S3/Redshift/EMR), Data Governance, Security/PII Compliance. Job qualifications Technical Skills - Experience with: AWS Redshift, Kafka, Data infrastructure and operations, Data pipeline. - You have experience in defining and implementing different types of data architecture, analyzing trade-offs and can define technology stacks for different types of data architecture. - You have exposure to designing application system architecture based on big data, artificial intelligence and related technologies. - You have experience in building, maintaining and tuning data platforms, as well as experience in data warehouse design, data modeling, data monitoring and maintenance. - You have experience with common design patterns, application frameworks and foundational/theoretical knowledge (i.e.: distributed systems, data intensive applications, etc.). - You are 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. - You have a good understanding of business and communication, collaboration skills, strong learning and summarizing abilities. - You have exposure to defining, developing and enabling data-driven techniques, advanced analytics, ML/AI and data mining applications in enterprise. - You have exposure to developing real-time and low-latency data streaming solutions. - You have exposure to productionizing machine learning models and applying techniques, tools and processes, and you are passionate about data infrastructure and operations, with expertise working in cloud environments. Professional Skills - You have experience influencing others and always advocate for technical excellence while being open to change when needed. - You bridge product and technology by helping to translate business needs to software requirements. - You have the ability to develop and execute a technical vision with a focus on business value. - You will act as a mentor for less experienced peers through both your technical knowledge and ability to inspire a team to deliver extraordinary impact together. - You are resilient in ambiguous situations and can approach challenges from multiple perspectives. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. EEO Statement Thoughtworks is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, ancestry, veteran status, or any other protected class. As a federal contractor, Thoughtworks is an affirmative action employer of protected veterans and individuals with disabilities. Extra important information Accommodations - Thoughtworks is committed to providing reasonable accommodations to applicants with disabilities and to applicants with sincerely held religious beliefs throughout the hiring process. If you need an accommodation to apply or participate in the interview process, please complete this form or speak with your recruiter. US - Work Authorization - Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment in the United States. Responsible Use of AI in Recruitment At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions. Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers. We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment. About Thoughtworks Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary. #LI-Remote Salary Benefits: https://www.thoughtworks.com/en-us/careers/benefits The annual salary range posted is subject to many factors and may vary depending on experience, geographic location, job responsibilities, performance, skills and/or training. Salary $173,000—$279,000 USD See here our AI policy.

• Plan and execute business-side data migration activities for Commercial and Procurement data objects in line with global and local deployment timelines • Coordinate and perform data cleansing activities, ensuring high data quality and adherence to defined standards • Collect, validate, and prepare data for migration, ensuring completeness, accuracy, and timely delivery • Collaborate with IT and technical teams to define and maintain data mappings between legacy systems and target solutions • Create and maintain master data lists for assigned Commercial and Procurement data objects • Provide business context and detailed input to support data extraction, transformation, and loading processes • Ensure data readiness across the full migration lifecycle through ongoing validation, quality checks, and issue resolution • Identify, track, and remediate data defects, inconsistencies, and anomalies • Validate that migrated data meets business requirements and is fit for purpose for operational processes • Perform manual data loads into target systems where required, following defined controls and procedures • Execute data validation checks and support approval processes for migrated data • Support testing phases (e.g., mock loads, system integration testing, user acceptance testing), including defect triage and resolution • Contribute to cutover activities, including final data loads, reconciliation, and validation • Collaborate with cross-functional stakeholders including business users, subject matter experts, and technical teams across multiple locations • Participate in project meetings, track progress, manage dependencies, and escalate risks and issues as needed • Ensure local business requirements and data specifics are captured and reflected in the migration approach

• Apoiar ativamente na definição de requisitos para a área de infraestrutura de TI/Dados, contribuindo com análises técnicas sobre soluções e alternativas propostas, avaliando impactos em performance, custo, escalabilidade e aderência à arquitetura existente; • Atuar com visão crítica moderada, sugerindo melhorias e identificando riscos técnicos, alinhado às diretrizes estabelecidas pelo time sênior e arquitetura corporativa; • Participar do desenho e implementação de arquiteturas de dados de média complexidade, seguindo padrões e diretrizes definidos pela arquitetura corporativa; • Atuar de forma colaborativa com equipes técnicas e não técnicas, traduzindo conceitos complexos em linguagem acessível para facilitar alinhamentos e decisões; • Contribuir ativamente para o sucesso dos projetos ao antecipar necessidades, apoiar outras áreas e participar da resolução de divergências técnicas com maturidade e foco em resultados; • Colaborar ativamente na definição e extração de dados provenientes de diferentes fontes para ingestão nas plataformas de Big Data, garantindo aderência aos padrões estabelecidos; • Apoiar a modelagem e organização das estruturas de dados para que estejam apropriadas, acessíveis e disponíveis para consumo, assegurando o alinhamento entre os dados operacionais e os modelos analíticos requeridos; • Contribuir ativamente nos projetos relacionados à integração de dados e sistemas, implementando soluções de média complexidade e garantindo aderência aos padrões arquiteturais definidos; • Apoiar o desenho técnico das soluções, participar da evolução da arquitetura existente e atua na manutenção e melhoria contínua dos sistemas sob sua responsabilidade.

• Responsible for integrating, analyzing raw data, developing, and maintaining datasets and improving data quality and efficiency. • Develops and maintains scalable data pipelines, integration tools and builds out new API integrations to support continuing increases in data usage, volume, and complexity. • Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition. • Designs data integrations, data quality framework and integrate it with monitoring services. • Strong hands on capabilities across integration toolsets including ADF, Replication, CDC etc. • Integrate data from different SOR’s, combine raw information and create resulting models ready for consumption. • Interpret trends and patterns. • Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. • Identifying, designing, and implementing internal process improvements including re-designing infrastructure for greater scalability, DB, SQL, and data pipelines performance tuning, optimizing data delivery, and automating manual processes. • Build solution prototypes as needed and write algorithms against data. • Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. • Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization. • Works closely with a team of frontend and backend engineers, product managers, and analysts.