
AI Data Architect
7 days ago
Role Overview
We are looking for an experienced AI Data Architect to design and implement robust, scalable, and secure data architectures that power AI/ML solutions. The role involves defining data strategies, enabling advanced analytics, ensuring data quality/governance, and optimizing infrastructure to support modern AI-driven applications.
Key Responsibilities
- Design and implement end-to-end data architectures to support AI/ML workloads.
- Define data strategy, governance, and frameworks for structured, semi-structured, and unstructured data.
- Architect scalable data pipelines, warehouses, and lakehouses optimized for AI/ML.
- Collaborate with Data Scientists, ML Engineers, and business teams to translate requirements into data architecture solutions.
- Ensure data security, compliance, lineage, and metadata management.
- Optimize data platforms for performance, scalability, and cost efficiency.
- Guide teams on best practices for integrating data platforms with AI/ML model training, deployment, and monitoring.
- Evaluate emerging tools and technologies in the Data & AI ecosystem.
Required Skills & Experience
- Proven experience as a Data Architect with a focus on AI/ML workloads.
- Strong expertise in cloud platforms (AWS, Azure, GCP) and cloud-native data services.
- Hands-on experience with data lakehouse architectures (Databricks, Snowflake, Delta Lake, BigQuery, Synapse).
- Proficiency in data pipeline frameworks (Apache Spark, Kafka, Airflow, DBT).
- Strong understanding of ML data lifecycle feature engineering, data versioning, training pipelines, MLOps.
- Knowledge of data governance frameworks, security, and compliance standards.
- Experience with SQL, Python, and distributed data systems.
- Familiarity with AI/ML platforms (SageMaker, Vertex AI, Azure ML) is a plus.
- Excellent problem-solving and stakeholder management skills.
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