Data Engineer
Analytics Engineer role focused on building and maintaining data pipelines, designing data models, and optimizing SQL queries using Python and cloud data warehouses like BigQuery and Snowflake. Requires strong ETL and workflow orchestration skills with Airflow.
Looking for Philippines-based candidates
Job Role: Analytics Engineer
Compensation range: $2,000 AUD - $3,000 AUD / Monthly
Engagement type: Independent Contractor Agreement
Work Schedule: This role is expected to align with the AU business hours (approx. 9 AM - 5 PM, Monday to Friday) for collaboration, but as a contractor, you’ll have flexibility in how you manage your time.
Who We Are: At Hunt St , we help Australian companies hire top remote talent in the Philippines. For this role, you will be engaged directly by the client as an independent contractor. We are not an outsourcing agency. All of our roles are 100% remote so you'll be able to work from home.
Who The Client Is: Our client is an independent technology consulting firm with over 15 years of experience helping organizations improve their systems, data, and workflows across industries such as manufacturing, healthcare, research, and laboratory environments. Rather than selling software, they provide unbiased consulting focused on system implementations, data migration, workflow optimization, and regulatory compliance. Their collaborative approach helps businesses modernize legacy systems, improve operational efficiency, and maximize the value of their existing technology so they can scale with confidence.
Role Overview: The analytics engineer builds the Gold layer and dbt Semantic Layer for each dataset phase. Where the senior data engineer builds the pipeline plumbing, the analytics engineer builds the business metrics — translating the metrics register definitions into governed, tested Gold models and MetricFlow metric definitions. This role sits closes to the business, requiring both technical depth and the ability to work directly with business stakeholders during metric validation sessions. The analytics engineer must be able to explain metric calculation choices in plain English, not just write the SQL. In Run steady state the analytics engineer role will take on support with AI monitoring responsibilities. New Gold model build volume drops significantly post go-live, freeing capacity for NLQ quality monitoring, LLM agent uptime, and Cortex ML model maintenance. Candidates should be comfortable with this evolution and ideally have some exposure to LLM API integration or ML monitoring.
Key Responsibilities:
Posted June 21, 2026