Data Architect

Job requirements

Experience Range:

With at least 7 to 10 years of experience in data architecture, data science, advanced statistical modeling, and AI architecture

Key Responsibilities:

- Design and architect robust data pipelines and frameworks to support advanced analytics, machine learning, and AI workloads

- Develop and implement statistical and AI models, including regression (linear and logistic), classification algorithms, forecasting techniques (ARIMA, exponential smoothing), and deep learning architectures

- Lead the integration of probabilistic graph models, advanced statistical tests (hypothesis testing, T-Test, Z-Test), and AI-driven solutions into production systems

- Collaborate with data scientists and engineering teams to optimize data workflows and AI model deployment using tools such as KubeFlow and BentoML

- Ensure data quality and integrity by implementing validation frameworks like Outstanding Expectations and Evidently AI

- Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS

- Evaluate and select appropriate machine learning and AI frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for scalable model deployment

- Provide technical leadership in the adoption of emerging technologies and best practices in data architecture, advanced analytics, and AI solutions

Required Skills:

- Advanced proficiency in Python and PySpark





- Expertise in statistical analysis and computing

- Hands-on experience with SAS and SPSS

- Strong knowledge of hypothesis testing, T-Test, and Z-Test

- Experience with regression techniques (linear and logistic)

- Proficiency in probabilistic graph models

- Familiarity with Great Expectations and Evidently AI for data validation

- Forecasting expertise using ARIMA, ARIMAX, and exponential smoothing

- Working knowledge of KubeFlow and BentoML

- Experience with classification algorithms (Decision Trees, SVM)

- Experience architecting AI solutions and deploying deep learning models

Preferred Skills:

- Advanced experience with ML and AI frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet

- Expertise in distance metrics (Hamming, Euclidean, Manhattan)

- Proficiency in R and R Studio

- Experience with scalable AI model deployment in cloud environments

- Knowledge of automated model monitoring, drift detection, and AI lifecycle management

Desired Qualifications:

- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline

- Certification in Data Architecture, Data Science, or AI (e.g., Certified Data Professional, Microsoft Certified: Azure Data Scientist Associate, AI Architect certification)

- Certification in Machine Learning frameworks or platforms (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty)

📌 Data Architect398 (Bengaluru)
🏢 Brillio
📍 Bengaluru