- Company Name
- Paragon Skills
- Job Title
- Head of Data, Automation & AI
- Job Description
-
**Job title**
Head of Data, Automation & AI
**Role Summary**
Lead the design, implementation, and scale of a modern data platform, AI, and automation capabilities to transform learning and operational processes. Build and guide a high‑impact team, set data strategy, and embed responsible AI practices across the organization.
**Expectations**
- Deliver enterprise‑scale data infrastructure and AI/automation initiatives within defined timelines.
- Drive continuous improvement of data governance, security, and ethical AI compliance.
- Foster a culture of data literacy, innovation, and learning across teams.
**Key Responsibilities**
- Architect and evolve a cloud‑based data lake/warehouse, ETL/ELT pipelines, and BI suite (Snowflake, Databricks, AWS/Azure/GCP, Microsoft Fabric).
- Design and implement real‑time streaming and lakehouse architectures; model data using dimensional and OLAP principles.
- Automate end‑to‑end business processes (Workato, Zapier, Power Automate, RPA) and integrate them with data workflows.
- Build, deploy, and maintain AI agents, NLP, recommendation engines, forecasting models, and generative AI solutions.
- Define and champion AI strategy, staff skill development, and leadership pipelines.
- Ensure compliance with data governance, privacy, and responsible AI regulations.
- Collaborate with product, operations, and learner‑experience teams to align data and AI initiatives with business objectives.
**Required Skills**
- Strategic leadership in data & AI transformation.
- Deep expertise in cloud data platforms (Snowflake, Databricks, AWS, GCP, Azure, MS Fabric).
- Proficiency with MLOps tools (MLflow, Airflow, dbt, Snowflake pipelines).
- Experience with automation platforms (Workato, Zapier, Power Automate).
- Knowledge of NLP, recommendation systems, forecasting, and generative AI.
- Strong data architecture, governance, dimensional modelling, lakehouse, and streaming concepts.
- Familiarity with AI ethics, regulatory compliance, and responsible AI practices.
**Required Education & Certifications**
- Degree in Computer Science, Data Science, Engineering, or related field (or equivalent professional training).
- Continuous professional development in data architecture, cloud platforms, advanced analytics, AI/ML, and data governance.
- Relevant certifications in cloud, data engineering, or AI (e.g., AWS/Azure/GCP certifications, Snowflake, Databricks, MLflow) are advantageous.