Design and implement robust data architecture frameworks for MDM & integration with enterprise
Build scalable data models and platforms to meet business and scientific needs.
Define and enforce standards for modelling, storage, metadata, and access.
Align architecture with AI/ML needs (feature stores, model serving, MLOps).
Embed the data governance to ensure compliance standards & security requirements are met
Set and maintain policies for data quality, security, privacy, and lifecycle.
Monitor compliance and support audits.
Work with stakeholders on stewardship, lineage, and metadata management.
Optimise data pipelines and workflows
Design and improve ETL/ELT for structured and multi‑modal data.
Increase processing efficiency and scalability for analytics and model training/serving.
Implement automation, observability, and monitoring.
Collaborate with cross‑functional teams
Partner with data scientists, engineers, and analysts to deliver production solutions.
Bridge technical and business stakeholders to align priorities.
Provide technical leadership and mentorship.
Evaluate and integrate emerging technologies
Assess and pilot new tools (knowledge graphs, vector DBs, distributed processing).
Lead integration of innovations into existing systems.
Track industry trends to drive continuous improvement.
Requirements
Minimum 10+ years of experience in data architecture, data engineering, or related roles.
Proven expertise in designing scalable data solutions, integrating AI/ML techniques, and working with structured and unstructured data.
Technical skills: Strong expertise with Informatica, Databricks, and data platforms (AWS, GCP, or Azure), distributed processing frameworks (e.g., Spark, Flink), and databases (relational, NoSQL, any).
Familiarity with data governance, advanced analytics, and data platforms.