We are seeking an experienced Senior Data Architect (AI) to design, implement, and optimize enterprise-grade data architectures that power our Artificial Intelligence (AI) and Machine Learning (ML) initiatives.
The ideal candidate will be responsible for defining data strategies, building scalable pipelines, ensuring data quality, and enabling advanced analytics and AI-driven decision-making across the organization.
This is a senior-level role requiring deep technical expertise, architectural vision, and the ability to collaborate with cross-functional teams including Data Engineers, Data Scientists, ML Engineers, and Business Stakeholders.
Key Responsibilities :
Data Architecture & Strategy :
- Design and implement end-to-end enterprise data architectures to support AI / ML use cases.
- Define data models, metadata standards, and data integration frameworks for structured, semi-structured, and unstructured data.
- Establish a roadmap for modern data platforms, ensuring alignment with AI-driven business strategies.
- Lead data modernization initiatives including migration to cloud-native platforms.
Data Engineering & Pipeline Management :
Architect and oversee development of data pipelines for ingestion, transformation, and storage of large-scale datasets from multiple sources.Ensure pipelines are optimized for real-time and batch AI / ML workloads.Define standards for data versioning, reproducibility, and feature store management for MLmodels.
Data Governance & Security :
Implement data governance frameworks ensuring compliance with security, privacy, and regulatory requirements (GDPR, HIPAA, etc.Establish best practices for data quality, lineage, cataloging, and stewardship.Enforce role-based access controls and encryption for sensitive datasets used in AI & Leadership :Partner with Data Scientists and ML Engineers to ensure models have reliable, scalable, and clean data.Collaborate with business stakeholders to translate requirements into technical data architecture solutions.Mentor junior data engineers / architects and guide teams on AI-ready data design & Optimization :Ensure data platforms and architectures are scalable, cost-efficient, and optimized for AI workloads.Evaluate emerging tools, frameworks, and vendors in the data & AI ecosystem.Drive proof-of-concepts (POCs) for new technologies and guide enterprise adoption.Required Technical Skills :
Data Architecture & Modeling : Dimensional modeling, data lakes, lakehouse, data warehouse design (Snowflake, Redshift, BigQuery, Synapse).Big Data & Distributed Systems : Spark, Hadoop, Databricks, Kafka, Flink.Cloud Platforms : AWS (Glue, Redshift, S3, SageMaker), Azure (Synapse, Data Factory, ML Studio), GCP (BigQuery, Dataflow, Vertex AI).Databases : Relational (PostgreSQL, MySQL, Oracle), NoSQL (MongoDB, Cassandra, DynamoDB), Graph DBs (Neo4j).AI / ML Integration : Experience with ML model lifecycle, feature stores (Feast, Tecton), and - MLOps frameworks.Programming / Scripting : SQL, Python, PySpark, Scala.Data Governance Tools : Collibra, Alation, Informatica, Apache Atlas.DevOps & Automation : CI / CD pipelines, Terraform, Kubernetes, Docker for deploying scalable data solutions.Soft Skills :
Strong problem-solving and analytical thinking with a strategic mindset.Excellent communication skills to articulate technical concepts to non-technical stakeholders.Leadership qualities with experience managing cross-functional technical teams(ref : hirist.tech)
