Solution Architect

Job Description Key Responsibilities Architecture & Design Translate business vision into robust, scalable, and secure architectures. Analyze functional and non-functional requirements to design end-to-end solutions. Develop architecture blueprints, reference models, and technical roadmaps. Ensure alignment of solution design with enterprise architecture standards and best practices. Innovation & Problem Solving Lead brainstorming and solution workshops with stakeholders. Evaluate emerging technologies, frameworks, and patterns to recommend innovative approaches. Apply out-of-the-box thinking to address business challenges with long-term value. Stakeholder Engagement Collaborate closely with business leaders, product managers, and delivery teams. Communicate complex technical solutions in a clear, business-friendly manner. Serve as a trusted advisor for clients and internal teams, guiding architecture decisions. Execution & Governance Provide technical leadership throughout the solution lifecycle, from design to deployment. Ensure architectural integrity, scalability, and maintainability in delivery. Conduct architecture reviews, risk assessments, and compliance checks. Requirements Key Requirements Minimum 10 years of experience in IT , including at least 3 years as a Solution Architect . Strong ability to translate business requirements (functional & non-functional) into scalable and effective architecture designs. Work experience of snowflake, spark and kafka. Expertise in designing enterprise-level, cloud-native, or hybrid solutions . Proven track record in brainstorming, ideation, and leading solution workshops . Deep understanding of Data engineering, AI engineering, software development practices, integration patterns, security, performance, and scalability . Hands-on knowledge of modern technologies (Cloud, AI/ML, Automation, Microservices, APIs, DevOps, etc.) . Strong communication, presentation, and stakeholder management skills. A strategic thinker with an innovative, solution-oriented mindset. Benefits At our organization, we believe success is built on responsiveness, integrity, and innovation . We foster a culture that values: Openness to learn and share knowledge Out-of-the-box thinking and creativity Responsibility and ownership at every level Collaboration across cultures and time zones Personal and professional growth alongside company growth You will find an exciting work environment , global exposure, and opportunities to contribute to transformative projects leveraging AI, automation, and consulting excellence . Compensation: Competitive MNC-level package with performance-based growth opportunities. Requirements Educational Background: Bachelor's and Master’s degrees in Data Science, Computer Science, Statistics, or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas, Scikit-Learn, TensorFlow, or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees, random forests, and gradient boosting machines. Competence in data preprocessing, cleaning, and analysis. Familiarity with data cleaning, transformation, and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction, and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel, Tableau, or more specialized software depending on the industry (e.g., SAS, SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP, Deep Learning, Machine Learning , Knowledge of genAI with implementation knowledge (LLM, fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS, Azure, Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis, forecasting, and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills, capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.