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
Salary:Max 36 LPA
Notice Period: Immediate joiners preferred
Experience: 12+ Years (minimum 45 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.
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