Data and AI Architect

About the job

Job Title: Data and AI Architect Must have Skill: Gen AI, Machine learning Models, AWS/ Azure, redshift, Python, Apachi, Airflow, Devops, minimum 4-5years experience as Architect, should be from Data Engineering background. Location: Bangalore / Mangalore Type: Full-Time CTC: Up to 36 LPA Notice Period: Immediate joiners preferred Experience: 12+ Years (minimum 4–5 years as Architect, Data Engineering background required) About the Role We are seeking an experienced Data & AI Architect to design and guide the implementation of scalable data platforms, AI/ML systems, and cloud-native architectures. This role bridges data engineering, data science, and enterprise architecture, ensuring that solutions are robust, secure, efficient, and aligned with business objectives. **Key Responsibilities** Data & AI Architecture - Design end-to-end architectures for data ingestion, storage, processing, analytics, and AI/ML workloads. - Architect data platforms such as data lakes, data warehouses, and lakehouses (Snowflake, Databricks, BigQuery, Redshift, etc.). - Define AI/ML architectures including model training, feature stores, deployment, and monitoring. - Build scalable real-time and batch data pipelines using modern frameworks (Kafka, Spark, Flink, Airflow, dbt). Solution Design & Governance - Develop conceptual, logical, and physical data models supporting advanced analytics and ML. - Ensure compliance with security, governance, quality, and regulatory requirements (GDPR, HIPAA, SOC2). - Establish data standards, best practices, and architectural guardrails. Collaboration & Stakeholder Leadership - Work closely with data scientists, ML engineers, data engineers, and business stakeholders to translate requirements into solution designs. - Lead architectural reviews and provide technical guidance during project execution. - Evaluate and recommend tools, cloud services, and platforms for data and AI initiatives. Cloud & Infrastructure - Define and optimize cloud-native architectures on AWS, Azure, or GCP. - Implement MLOps/ModelOps practices including CI/CD for models, monitoring, and lifecycle management. - Architect solutions with scalability, performance, availability, and cost-efficiency in mind. **Key Skills** - Strong hands-on background in data engineering, analytics, or data science. - Expertise in building data platforms using: - Cloud: AWS (Glue, S3, Redshift), Azure (Data Factory, Synapse), GCP (BigQuery, Dataflow) - Compute: Spark, Databricks, Flink - Data Modelling: Dimensional, Relational, NoSQL, Graph - Proficiency with Python, SQL, and data pipeline orchestration tools (Airflow, dbt). - Understanding of ML frameworks and tools: TensorFlow, PyTorch, Scikit-learn, MLflow. - Experience implementing MLOps, model deployment, monitoring, logging, and versioning. **Soft Skills** - Strong communication skills with ability to translate technical concepts into business terms. - Leadership and mentoring capabilities. - Problem-solving mindset with a focus on scalable, future-proof design. **Preferred Qualifications** - 8+ years of experience in data engineering, data science, or architecture roles. - Experience designing enterprise-grade AI platforms. - Certification in major cloud platforms (AWS/Azure/GCP). - Experience with governance tooling (Collibra, Alation) and lineage systems.

Requirements

• Gen AI
• Machine Learning Models
• AWS
• Azure
• Python
• Airflow
• DevOps

Qualifications

• 4-5 years as Architect
• Data Engineering background

Preferred Technologies

• Gen AI
• Machine Learning Models
• AWS
• Azure
• Python
• Airflow
• DevOps