Data Architect - R01570398

Brillio; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Brillio in Bengaluru seeks a highly experienced Data Architect to design robust data pipelines for advanced analytics, ML, and AI workloads. The role requires building statistical and AI models including regression, forecasting, and deep learning.

Lead integration of probabilistic graphs, validation frameworks, and AI-driven solutions into production, collaborating with data scientists and engineers to optimize workflows and model deployment.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or related discipline.
• Certifications in Data Architecture, Data Science, or AI (e.g., Certified Data Professional, Azure Data Scientist Associate).
• Certifications in ML frameworks or platforms (e.g., TensorFlow Developer Certificate, AWS ML Specialty).

Responsibilities

• Design and architect robust data pipelines and frameworks to support advanced analytics, ML, and AI workloads.
• Develop and implement statistical and AI models, including regression, forecasting, and deep learning.
• Lead the integration of probabilistic graph models and AI-driven solutions into production systems.
• Collaborate with data scientists and engineers to optimize data workflows and AI model deployment (KubeFlow, BentoML).
• Ensure data quality by implementing validation frameworks like Great Expectations and Evidently AI.
• Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS.
• Evaluate and select frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for deployment.
• Provide technical leadership in adoption of emerging technologies and best practices in data architecture and AI.

Skills

Python

PySpark

Statistics

Hypothesis testing

Regression

Probabilistic graphs

Great Expectations

Evidently AI

KubeFlow

BentoML

Classification

Deep learning

R

Cloud deployment

Model monitoring

Education

Bachelor's degree

Data Architecture certification

ML framework certs

Tools

SAS

SPSS

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

R Studio

Job description

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 Great 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)