Jobs at INTELLIGEN

Hands-on data engineer working with clients to re-engineer, optimise and domain-align data models and pipelines using Snowflake and dbt. Contribute to solution design, performance tuning, CI/CD, testing, documentation, and collaborate within consulting delivery teams to ensure maintainability and lineage.

Lead client engagements to design and implement practical AI governance frameworks, assess AI use cases for risk and compliance, embed governance into AI solution design, facilitate stakeholder workshops, and develop governance artefacts to enable responsible, scalable AI adoption.

Partner with clients to translate business goals into secure, scalable AI and data solution architectures. Design integrations, data flows, APIs, and governance-aligned architectures; facilitate workshops; produce artefacts and guide delivery teams.

Lead design and delivery of modern cloud data platforms and scalable pipelines. Improve platform stability, implement data models and governance, support data product development, mentor junior consultants, and collaborate with stakeholders to translate business needs into reliable, automated data solutions.

Work with stakeholders to discover practical AI use cases, prototype and deliver lightweight LLM-enabled agents, troubleshoot and refine solutions, facilitate stakeholder adoption and training, and ensure responsible AI governance. Own projects from discovery through delivery to measurable outcomes while communicating trade-offs and limitations clearly.

Design, build, and optimize end-to-end data pipelines and cloud data platforms. Implement ETL/ELT, ensure data quality, governance, and security, collaborate with architects and stakeholders, and support analytics and AI initiatives within agile, client-facing engagements.

Hands-on data engineer to re-engineer and optimise dbt models and Snowflake data warehouses. Responsibilities include schema design, performance tuning, domain-aligned modelling, CI/CD, testing, documentation, and collaborating with client teams and consulting peers to deliver maintainable pipelines.

Design and maintain conceptual, logical and physical data models using Data Vault and Kimball approaches. Write and optimise complex SQL, use Databricks for data preparation, support integration and validation, run modelling workshops with stakeholders, translate requirements into scalable models, and drive delivery while managing priorities and stakeholder expectations.

Design and deliver scalable multi-cloud data solutions using Databricks/Snowflake and modern data stacks. Build ingestion, transformation, modelling and access layers, implement dbt and CI/CD, ensure data quality, governance and lineage, support analytics and AI enablement, and consult directly with clients while mentoring junior engineers.