Senior Data Engineer (014-851) at Hunt St

, , Philippines -

Full Time

Start Date

Immediate

Expiry Date

04 Aug, 26

Salary

3500.0

Posted On

06 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Databricks, Microsoft Fabric, ETL/ELT, Medallion Architecture, Dimensional Modelling, CI/CD, Git, AI-assisted Tooling, Prompt Design, Data Pipeline Design, Lakehouse Architecture, API Integration, SCDs, Star Schemas

Industry

Staffing and Recruiting

Description

Looking for Philippines-based candidates Job Role: Senior Data Engineer Compensation range: $2,500 AUD - $3,500 AUD / Monthly Engagement type: Employer of Record Work Schedule: This role is expected to align with the AU business hours (approx. 9 AM - 5 PM, Monday to Friday). Who We Are: At Hunt St, we help Australian companies hire top remote talent in the Philippines. For this role, you will be formally employed through an Employer of Record (EOR) arrangement. 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: A boutique Australia-based consulting team specialising in data engineering, analytics, and AI-driven solutions for a diverse client base across industries such as financial services, healthcare, retail, and technology. Role Overview: We’re looking for a Senior Data Engineer to join a high-performing delivery team and work on end-to-end data solutions across modern lakehouse environments. This is a hands-on role, focused on building and shipping production pipelines—not people management. You’ll work directly with clients and senior engineers, owning delivery from ingestion through to transformation and consumption. Key Responsibilities: Design, build, and maintain scalable data pipelines in modern lakehouse architectures. Develop clean, efficient, and production-ready Python and SQL code. Implement ETL/ELT processes, transformations, and orchestration workflows. Model data using medallion architecture (Bronze/Silver/Gold), star schemas, and SCDs. Integrate multiple data sources (APIs, databases, SaaS platforms, flat files). Deploy pipelines using CI/CD tools and version control best practices. Leverage AI tools (e.g., agent-based workflows, automation scripts) to improve delivery speed and quality. Collaborate directly with clients on requirements, architecture, and delivery updates. Monitor, troubleshoot, and optimise pipelines for performance and reliability. Ensure data quality, integrity, and production readiness. Required Skills and Qualifications: 5+ years of professional experience in data engineering. Must have experience with Databricks or Fabric. Strong Python skills for production environments. Advanced SQL (CTEs, window functions, performance tuning, complex joins). Hands-on experience with modern data platforms (lakehouse, pipelines, distributed processing). Experience with dimensional modelling and analytics-ready data design. Solid understanding of CI/CD, Git workflows, and deployment practices. Strong communication skills with the ability to work directly with clients. Ability to translate business requirements into technical solutions. AI Proficiency (Required) This role requires strong, practical experience using AI in development workflows: Comfortable working in modern development environments with AI-assisted tooling. Proven experience building AI-powered tools, automations, or agents with real business impact. Ability to use AI across the development lifecycle (design, coding, debugging, testing, documentation). Strong judgment in validating and refining AI-generated outputs. Experience with prompt design, context handling, and tool integrations. Nice to Have Experience with integration platforms or middleware tools. Exposure to dbt or modern data transformation frameworks. Experience with cloud-based data ecosystems. Dashboarding or semantic modelling experience. Familiarity with AI/agent frameworks or orchestration tools. Previous consulting or client-facing project delivery. Work Arrangement & Expectations: This is a remote role that will be set up as an employer of record. 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

Responsibilities

Design and maintain scalable data pipelines within modern lakehouse environments using Python and SQL. Own the end-to-end delivery process from data ingestion and transformation to final consumption for clients.