Client: Australian & New Zealand company that designs custom window furnishings for beautiful spaces.

About the role

The client is a growing Window Furnishings company that relies on data to drive key decisions. We are looking for an Data Engineer to design, build, and optimize our data pipelines and semantic layer, ensuring our teams have reliable, well-defined business metrics at their fingertips.

You will work closely with software developers, analysts, and business stakeholders to define core metrics, transform raw data into useful models, and build a scalable analytics infrastructure using modern data tools like SQLMesh (or dbt) and Cube.

Key Responsibilities

• Design & build robust data pipelines to ingest, transform, and model data efficiently.
• Implement dbt for transformation workflows and data versioning.
• Collaborate with stakeholders to understand reporting needs and define clear KPIs.
• Optimize data models for performance, scalability, and cost efficiency.
• Ensure data governance and quality by implementing testing, monitoring, and documentation.
• Integrate data from multiple sources into our Redshift data warehouse.
• Improve query performance and ensure real-time analytics capabilities as needed.

Requirements:

• 3+ years of experience in Analytics Engineering, Data Engineering, or BI Engineering.
• Strong SQL skills and experience with data modelling (Star/Snowflake schema).
• Hands-on experience with dbt, SQLMesh, or similar transformation frameworks.
• Knowledge of Cube, LookML, MetricFlow, or other semantic layer tools.
• Experience working with data warehouses (BigQuery, Snowflake, Redshift, etc.).
• Familiarity with ETL/ELT processes and workflow orchestration (Airflow, Dagster).
• Strong understanding of data governance, testing, and version control (e.g., CI/CD for data).
• Ability to work closely with business teams to define meaningful and actionable metrics.
• Excellent communication skills and a passion for scalable, high-quality data systems.

Nice to have:

• Experience with streaming data pipelines (Kafka, Flink, etc.)
• Familiarity with Python for data engineering
• Experience with data visualization tools (Metabase, Tableau, Power BI, Looker)

Work Details:

• Work Schedule: Monday – Friday 5:30AM – 2:30PM
• Work Setup: Hybrid | Trafalgar Bldg. Salcedo Village, Makati City
• Full-Time: Project based (3-6mos duration)