- Company Name
- Knovia
- Job Title
- Head of Data, Automation & AI
- Job Description
-
Job title: Head of Data, Automation & AI
Role Summary
Lead the design, implementation, and operation of an enterprise‑level data platform and AI/automation strategy. Build and manage a high‑impact team to modernise data infrastructure, automate core business processes, and embed AI across learning and operations to drive efficiency and learner outcomes.
Expectations
* Deliver scalable, cloud‑based data architecture (lake, lakehouse, warehouse).
* Design and deploy end‑to‑end automation and AI solutions that align with organisational goals.
* Champion data governance, security, and responsible AI practices.
* Build internal capability through coaching, training, and knowledge sharing.
Key Responsibilities
1. Oversee evolution of a modern data platform (data lake, warehouse, pipelines, BI suite).
2. Lead end‑to‑end automation of business processes (e.g., Workato, Zapier, Power Automate).
3. Architect, develop, and operate AI agents, including NLP, recommendation, forecasting, and generative models.
4. Enhance analytics capabilities to improve customer insights and operational decisions.
5. Govern data integrity, security, compliance, and ethical AI standards.
6. Manage vendor relationships with cloud providers (AWS, GCP, Azure, Microsoft Fabric) and big‑data tools (Snowflake, Databricks).
7. Provide technical leadership, mentoring, and performance management for a data, AI, and automation team.
8. Drive continuous improvement of ETL/ELT pipelines, MLOps pipelines, and real‑time streaming architectures.
Required Skills
* Proven senior leadership in data, AI, or digital transformation.
* Expertise in cloud data platforms: Snowflake, Databricks, AWS/GCP/Azure, Microsoft Fabric.
* Strong data engineering, pipeline design, MLOps, and ETL/ELT architecture.
* Experience with workflow orchestration (Airflow, dbt, MLflow).
* Knowledge of automation tools (Workato, Zapier, Power Automate) and RPA concepts.
* Proficiency in AI/ML concepts: NLP, recommendation engines, forecasting, generative AI.
* Deep understanding of data governance, security, and compliance (GDPR, HDS, etc.).
* Familiarity with AI ethics, responsible AI, and regulatory frameworks.
* Excellent communication, stakeholder management, and strategic thinking.
Required Education & Certifications
* Bachelor’s (or higher) degree in Computer Science, Data Science, Engineering, or related discipline (or equivalent professional training).
* Continuous professional development evidence in data architecture, cloud services, advanced analytics, and AI.
* Relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer, GCP Professional Data Engineer) are advantageous.