About the role
We are currently looking for a Senior Data Engineer to strengthen our data platform and build reliable, scalable data solutions that support business decision-making. This is a senior individual contributor role requiring strong hands-on engineering skills, ownership of data pipelines and architecture, and expertise in data integration, Snowflake, and dbt. You will work across engineering and business teams to improve data quality, platform reliability, and performance while exploring AI-enabled data engineering practices.
Responsibilities:
- Design, develop, and optimise scalable data pipelines and integration frameworks.
- Build and maintain data integrations using tools such as Fivetran and custom pipelines.
- Architect and develop data models in Snowflake using dbt to support revenue, operational, and analytical use cases.
- Define standards for data ingestion, orchestration, transformation, and warehouse architecture.
- Ensure data consistency and integrity across source systems, ingestion layers, and warehouse models.
- Implement data quality checks, automated testing, monitoring, documentation, and data lineage.
- Optimise pipeline performance, warehouse efficiency, and data processing costs.
- Collaborate with cross-functional teams to translate complex business and technical requirements into scalable data solutions.
- Leverage AI tools to accelerate engineering workflows, improve monitoring and optimisation, and enable trusted AI-driven data consumption.
- Establish appropriate validation practices and guardrails for responsible AI usage.
Requirements:
- Strong hands-on experience in Data Engineering, data integration, and data pipeline development.
- Expertise in SQL, Snowflake, and dbt for data transformation and modelling.
- Experience building and maintaining data pipelines using Fivetran or similar integration tools, alongside custom-built pipelines.
- Strong understanding of data warehouse architecture, ingestion frameworks, orchestration, and transformation layers.
- Experience implementing data quality checks, testing, monitoring, and pipeline reliability practices.
- Ability to troubleshoot complex data issues and optimise query performance and processing costs.
- Experience designing scalable, reusable data models and engineering standards.
- Strong ownership, problem-solving, and stakeholder collaboration skills.
- Ability to work independently and drive technical decisions in an evolving environment.
Good to Have:
- Experience with AI-assisted engineering workflows and AI-ready data architectures.
- Familiarity with cloud data platforms and modern data stack technologies.
- Exposure to data governance, lineage, observability, and responsible AI practices.
Ideal Candidate:
- A hands-on Senior Data Engineer who has built and scaled data pipelines, developed Snowflake and dbt models, integrated multiple source systems, and established reliable data quality practices.
- The candidate should be comfortable owning technical decisions and improving the data platform as a senior individual contributor.