Senior Data Engineer

Looking for Philippines-based candidates

Job Role: Senior Data Engineer

Compensation range: $2,000-3,000 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 youll 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 senior data engineer is the Silver layer builder for each dataset Build phase. Paired with the analytics engineer, they take the Bronze tables delivered by the IT team and transform them into clean, tested, conformed Silver models in Snowflake. They make the structural and technical decisions for each dataset, grain, primary keys, incremental strategy, schema design, so the analytics engineer can focus on the business metric layer above.

In Run state the senior data engineer owns pipeline incident response. When a schema change breaks a Bronze-to-Silver mapping, they fix it. When a Snowflake pipeline degrades and queries start timing out, they identify the cause and resolve it. They are the person the Run team turns to when the AI triage layer escalates a genuine pipeline failure.

Key Responsibilities:

• Build Silver layer dbt models for each dataset phase, staging models, intermediate models, and conformed fact and dimension tables
• Define and implement incremental load strategies for each entity, upsert logic, snapshot tables, and data freshness handling
• Write and maintain dbt schema tests, not-null, uniqueness, referential integrity, accepted values, and custom generic tests
• Collaborate with the analytics engineer on the Silver-to-Gold interface, ensuring Silver models expose the fields and grain needed for Gold metric calculations
• Work with IT during each phase, confirming entity availability, field mappings, and Bronze table quality before build commences
• In Run steady state: own pipeline incident response, schema drift handling, and Snowflake performance monitoring across all live datasets

Run & Steady-State Responsibilities:

• Investigate and resolve pipeline incidents escalated by the AI triage layer.
• Manage upstream schema changes affecting Bronze-to-Silver mappings.
• Monitor and optimize Snowflake query performance across live Gold datasets.
• Own and maintain the AI triage pipeline, ensuring alert classification accuracy and incident log completeness.
• Ensure escalated alerts are acknowledged and resolved within agreed SLA timelines.
• Maintain accurate data catalogue documentation and quality certifications across production Gold datasets.

Requirements

• 4-6 years Data Engineering experience
• Snowflake advanced: incremental models, time travel, merge statements, clustering, zero- copy cloning for test environments
• dbt advanced: macros, packages, generic tests, snapshots, sources, exposures, CI/CD integration
• SQL expert: complex joins, window functions, handling late-arriving data, query performance optimisation
• Python intermediate: Snowpark for custom transformations where SQL is insufficient
• Git proficient: branching strategy, pull requests, conflict resolution in a shared dbt project
• Retail data structures intermediate: order headers and lines, inventory snapshots, customer master, fiscal calendars
• AI & Automation Tools: Hands-on experience with tools such as GitHub Copilot, Cursor, Claude (or similar LLMs), Snowflake Cortex AI_COMPLETE, Elementary, and data observability platforms for AI-assisted development, SQL debugging, anomaly detection, alert classification, incident reporting, and workflow automation.

What Success Looks Like:

• Passionate about building and maintaining a modern, scalable data platform.
• Proven experience developing incremental dbt models in Snowflake, with a strong understanding of data modeling trade-offs, dependencies, and shared engineering workflows.
• Able to assess source schemas, monitor pipeline health, manage alert noise, and maintain reliable data operations across live datasets.
• Strong communicator who can translate technical incidents into clear, concise updates for non-technical stakeholders.
• Comfortable in a highly operational role focused on platform stability, proactive issue resolution, and appropriate escalation management.

Work Arrangement & Expectations:

This is a remote role that will be set up as an independent contractor engagement.

To ensure alignment and transparency, successful candidates will be expected to:

• Disclose any existing ongoing roles or client work
• Reflect this engagement on their LinkedIn profile (clearly marked as “Independent Contractor”)