Analytics Engineer Consultant

About the role

Sia Hong Kong is recruiting an Analytics Engineer Consultant, a profile at the intersection of data analysis and data engineering. You will work with clients to turn raw data into actionable data products and usable analyses with strong business impact, acting as a key contact for business teams on modelling, reliability and decision support.

Key responsibilities

• Gather and understand business needs and propose technical solutions (analytics tools, data models, workflow automation, dashboards).
• Design robust and scalable data models.
• Build and optimise ETL/ELT pipelines to automate flows between sources and analytics platforms.
• Industrialise data products (dashboards, APIs, exports, analytical models) and ensure their maintainability, adoption and documentation.
• Put data governance in place (quality, traceability, monitoring).
• Train and support users (business teams, analysts, data scientists) in using the tools and assets developed.
• Take part in every stage of the project, from diagnosis through production rollout and change management.
• Internal activities: contribute to training, working groups and R&D, publish sector blogs and studies, and support business development.

Required profile

• Master's degree (Bac+5) from an engineering or business school, with a specialisation in data science, statistics or marketing.
• 1 to 3 years of experience in a similar role or in the data field.
• Fluency in English is essential; business-level Mandarin or Cantonese is highly advantageous.
• An interest in business topics such as marketing, finance, logistics, energy, transport, industry or CSR.

Required skills

• Advanced SQL and data transformation tools.
• Experience with at least one cloud environment (AWS, GCP or Azure).
• Strong command of dimensional modelling and schema design.
• Desirable: Terraform, Snowflake, Redshift, dbt, Airflow, Power BI, Tableau, Git, CI/CD, analytics testing.

What we offer

• High-impact engagements across sectors such as financial services, luxury, transport, retail and consumer goods.
• Data training courses and certifications.
• A dynamic, cross-sector environment with internal R&D topics.
• A company committed to the climate transition.